Merge branch 'develop' into anl-ne-requests

docs/source/pythonapi/index.rst

@@ -27,6 +27,8 @@ Example Jupyter Notebooks
     examples/mgxs-part-ii
     examples/mgxs-part-iii
     examples/mgxs-part-iv
+    examples/mdgxs-part-i
+    examples/mdgxs-part-ii
     examples/nuclear-data
 
 ------------------------------------
@@ -284,6 +286,19 @@ Multi-group Cross Sections
     openmc.mgxs.TotalXS
     openmc.mgxs.TransportXS
 
+Multi-delayed-group Cross Sections
+----------------------------------
+
+.. autosummary::
+    :toctree: generated
+    :nosignatures:
+    :template: myclassinherit.rst
+
+    openmc.mgxs.MDGXS
+    openmc.mgxs.ChiDelayed
+    openmc.mgxs.DelayedNuFissionXS
+    openmc.mgxs.Beta
+
 Multi-group Cross Section Libraries
 -----------------------------------
 

openmc/__init__.py

@@ -13,10 +13,10 @@ from openmc.settings import *
 from openmc.surface import *
 from openmc.universe import *
 from openmc.mesh import *
-from openmc.mgxs_library import *
 from openmc.filter import *
 from openmc.trigger import *
 from openmc.tallies import *
+from openmc.mgxs_library import *
 from openmc.cmfd import *
 from openmc.executor import *
 from openmc.statepoint import *

openmc/filter.py

@@ -777,6 +777,18 @@ class Filter(object):
             df.loc[:, self.type + ' low'] = lo_bins
             df.loc[:, self.type + ' high'] = hi_bins
 
+        elif self.type == 'surface':
+            filter_bins = np.repeat(self.bins, self.stride)
+            tile_factor = data_size / len(filter_bins)
+            filter_bins = np.tile(filter_bins, tile_factor)
+            filter_bins = [x if x != 1 else 'x-min' for x in filter_bins]
+            filter_bins = [x if x != 2 else 'x-max' for x in filter_bins]
+            filter_bins = [x if x != 3 else 'y-min' for x in filter_bins]
+            filter_bins = [x if x != 4 else 'y-max' for x in filter_bins]
+            filter_bins = [x if x != 5 else 'z-min' for x in filter_bins]
+            filter_bins = [x if x != 6 else 'z-max' for x in filter_bins]
+            df = pd.concat([df, pd.DataFrame({self.type : filter_bins})])
+
         # universe, material, surface, cell, and cellborn filters
         else:
             filter_bins = np.repeat(self.bins, self.stride)

openmc/mgxs/__init__.py

@@ -1,3 +1,4 @@
 from openmc.mgxs.groups import EnergyGroups
 from openmc.mgxs.library import Library
 from openmc.mgxs.mgxs import *
+from openmc.mgxs.mdgxs import *

openmc/mgxs/library.py

@@ -11,6 +11,7 @@ import numpy as np
 import openmc
 import openmc.mgxs
 import openmc.checkvalue as cv
+from openmc.tallies import ESTIMATOR_TYPES
 
 
 if sys.version_info[0] >= 3:
@@ -18,17 +19,18 @@ if sys.version_info[0] >= 3:
 
 
 class Library(object):
-    """A multi-group cross section library for some energy group structure.
+    """A multi-energy-group and multi-delayed-group cross section library for
+    some energy group structure.
 
     This class can be used for both OpenMC input generation and tally data
     post-processing to compute spatially-homogenized and energy-integrated
     multi-group cross sections for deterministic neutronics calculations.
 
-    This class helps automate the generation of MGXS objects for some energy
-    group structure and domain type. The Library serves as a collection for
-    MGXS objects with routines to automate the initialization of tallies for
-    input files, the loading of tally data from statepoint files, data storage,
-    energy group condensation and more.
+    This class helps automate the generation of MGXS and MDGXS objects for some
+    energy group structure and domain type. The Library serves as a collection
+    for MGXS and MDGXS objects with routines to automate the initialization of
+    tallies for input files, the loading of tally data from statepoint files,
+    data storage, energy group condensation and more.
 
     Parameters
     ----------
@@ -39,7 +41,7 @@ class Library(object):
     mgxs_types : Iterable of str
         The types of cross sections in the library (e.g., ['total', 'scatter'])
     name : str, optional
-        Name of the multi-group cross section. library Used as a label to
+        Name of the multi-group cross section library. Used as a label to
         identify tallies in OpenMC 'tallies.xml' file.
 
     Attributes
@@ -64,6 +66,11 @@ class Library(object):
         The highest legendre moment in the scattering matrices (default is 0)
     energy_groups : openmc.mgxs.EnergyGroups
         Energy group structure for energy condensation
+    delayed_groups : list of int
+        Delayed groups to filter out the xs
+    estimator : str or None
+        The tally estimator used to compute multi-group cross sections. If None,
+        the default for each MGXS type is used.
     tally_trigger : openmc.Trigger
         An (optional) tally precision trigger given to each tally used to
         compute the cross section
@@ -95,6 +102,7 @@ class Library(object):
         self._domain_type = None
         self._domains = 'all'
         self._energy_groups = None
+        self._delayed_groups = None
         self._correction = 'P0'
         self._legendre_order = 0
         self._tally_trigger = None
@@ -102,6 +110,7 @@ class Library(object):
         self._sp_filename = None
         self._keff = None
         self._sparse = False
+        self._estimator = None
 
         self.name = name
         self.openmc_geometry = openmc_geometry
@@ -126,6 +135,7 @@ class Library(object):
             clone._correction = self.correction
             clone._legendre_order = self.legendre_order
             clone._energy_groups = copy.deepcopy(self.energy_groups, memo)
+            clone._delayed_groups = copy.deepcopy(self.delayed_groups, memo)
             clone._tally_trigger = copy.deepcopy(self.tally_trigger, memo)
             clone._all_mgxs = copy.deepcopy(self.all_mgxs)
             clone._sp_filename = self._sp_filename
@@ -194,6 +204,10 @@ class Library(object):
     def energy_groups(self):
         return self._energy_groups
 
+    @property
+    def delayed_groups(self):
+        return self._delayed_groups
+
     @property
     def correction(self):
         return self._correction
@@ -206,10 +220,21 @@ class Library(object):
     def tally_trigger(self):
         return self._tally_trigger
 
+    @property
+    def estimator(self):
+        return self._estimator
+
     @property
     def num_groups(self):
         return self.energy_groups.num_groups
 
+    @property
+    def num_delayed_groups(self):
+        if self.delayed_groups == None:
+            return 0
+        else:
+            return len(self.delayed_groups)
+
     @property
     def all_mgxs(self):
         return self._all_mgxs
@@ -239,22 +264,33 @@ class Library(object):
 
     @mgxs_types.setter
     def mgxs_types(self, mgxs_types):
+        all_mgxs_types = openmc.mgxs.MGXS_TYPES + openmc.mgxs.MDGXS_TYPES
         if mgxs_types == 'all':
-            self._mgxs_types = openmc.mgxs.MGXS_TYPES
+            self._mgxs_types = all_mgxs_types
         else:
             cv.check_iterable_type('mgxs_types', mgxs_types, basestring)
             for mgxs_type in mgxs_types:
-                cv.check_value('mgxs_type', mgxs_type, openmc.mgxs.MGXS_TYPES)
+                cv.check_value('mgxs_type', mgxs_type, all_mgxs_types)
             self._mgxs_types = mgxs_types
 
     @by_nuclide.setter
     def by_nuclide(self, by_nuclide):
         cv.check_type('by_nuclide', by_nuclide, bool)
+
+        if by_nuclide == True and self.domain_type == 'mesh':
+            raise ValueError('Unable to create MGXS library by nuclide with '
+                             'mesh domain')
+
         self._by_nuclide = by_nuclide
 
     @domain_type.setter
     def domain_type(self, domain_type):
         cv.check_value('domain type', domain_type, openmc.mgxs.DOMAIN_TYPES)
+
+        if self.by_nuclide == True and domain_type == 'mesh':
+            raise ValueError('Unable to create MGXS library by nuclide with '
+                             'mesh domain')
+
         self._domain_type = domain_type
 
     @domains.setter
@@ -298,6 +334,23 @@ class Library(object):
         cv.check_type('energy groups', energy_groups, openmc.mgxs.EnergyGroups)
         self._energy_groups = energy_groups
 
+    @delayed_groups.setter
+    def delayed_groups(self, delayed_groups):
+
+        if delayed_groups != None:
+
+            cv.check_type('delayed groups', delayed_groups, list, int)
+            cv.check_greater_than('num delayed groups', len(delayed_groups), 0)
+
+            # Check that the groups are within [1, MAX_DELAYED_GROUPS]
+            for group in delayed_groups:
+                cv.check_greater_than('delayed group', group, 0)
+                cv.check_less_than('delayed group', group,
+                                   openmc.mgxs.MAX_DELAYED_GROUPS,
+                                   equality=True)
+
+            self._delayed_groups = delayed_groups
+
     @correction.setter
     def correction(self, correction):
         cv.check_value('correction', correction, ('P0', None))
@@ -327,6 +380,11 @@ class Library(object):
         cv.check_type('tally trigger', tally_trigger, openmc.Trigger)
         self._tally_trigger = tally_trigger
 
+    @estimator.setter
+    def estimator(self, estimator):
+        cv.check_value('estimator', estimator, ESTIMATOR_TYPES)
+        self._estimator = estimator
+
     @sparse.setter
     def sparse(self, sparse):
         """Convert tally data from NumPy arrays to SciPy list of lists (LIL)
@@ -363,14 +421,23 @@ class Library(object):
         for domain in self.domains:
             self.all_mgxs[domain.id] = OrderedDict()
             for mgxs_type in self.mgxs_types:
-                mgxs = openmc.mgxs.MGXS.get_mgxs(mgxs_type, name=self.name)
+                if mgxs_type in openmc.mgxs.MDGXS_TYPES:
+                    mgxs = openmc.mgxs.MDGXS.get_mgxs(mgxs_type, name=self.name)
+                else:
+                    mgxs = openmc.mgxs.MGXS.get_mgxs(mgxs_type, name=self.name)
+
                 mgxs.domain = domain
                 mgxs.domain_type = self.domain_type
                 mgxs.energy_groups = self.energy_groups
                 mgxs.by_nuclide = self.by_nuclide
+                if self.estimator is not None:
+                    mgxs.estimator = self.estimator
+
+                if mgxs_type in openmc.mgxs.MDGXS_TYPES:
+                    mgxs.delayed_groups = self.delayed_groups
 
                 # If a tally trigger was specified, add it to the MGXS
-                if self.tally_trigger:
+                if self.tally_trigger is not None:
                     mgxs.tally_trigger = self.tally_trigger
 
                 # Specify whether to use a transport ('P0') correction
@@ -460,7 +527,7 @@ class Library(object):
         ----------
         domain : Material or Cell or Universe or Integral
             The material, cell, or universe object of interest (or its ID)
-        mgxs_type : {'total', 'transport', 'nu-transport', 'absorption', 'capture', 'fission', 'nu-fission', 'kappa-fission', 'scatter', 'nu-scatter', 'scatter matrix', 'nu-scatter matrix', 'multiplicity matrix', 'nu-fission matrix', chi', 'chi-prompt', 'inverse-velocity', 'prompt-nu-fission'}
+        mgxs_type : {'total', 'transport', 'nu-transport', 'absorption', 'capture', 'fission', 'nu-fission', 'kappa-fission', 'scatter', 'nu-scatter', 'scatter matrix', 'nu-scatter matrix', 'multiplicity matrix', 'nu-fission matrix', chi', 'chi-prompt', 'inverse-velocity', 'prompt-nu-fission', 'delayed-nu-fission', 'chi-delayed', 'beta'}
             The type of multi-group cross section object to return
 
         Returns
@@ -763,7 +830,7 @@ class Library(object):
 
         Parameters
         ----------
-        domain : openmc.Material or openmc.Cell or openmc.Universe
+        domain : openmc.Material or openmc.Cell or openmc.Universe or openmc.Mesh
             The domain for spatial homogenization
         xsdata_name : str
             Name to apply to the "xsdata" entry produced by this method
@@ -811,7 +878,7 @@ class Library(object):
         """
 
         cv.check_type('domain', domain, (openmc.Material, openmc.Cell,
-                                         openmc.Cell))
+                                         openmc.Cell, openmc.Mesh))
         cv.check_type('xsdata_name', xsdata_name, basestring)
         cv.check_type('nuclide', nuclide, basestring)
         cv.check_value('xs_type', xs_type, ['macro', 'micro'])

openmc/mgxs/mgxs.py

@@ -13,6 +13,7 @@ import numpy as np
 
 import openmc
 import openmc.checkvalue as cv
+from openmc.tallies import ESTIMATOR_TYPES
 from openmc.mgxs import EnergyGroups
 
 if sys.version_info[0] >= 3:
@@ -39,7 +40,6 @@ MGXS_TYPES = ['total',
               'inverse-velocity',
               'prompt-nu-fission']
 
-
 # Supported domain types
 DOMAIN_TYPES = ['cell',
                 'distribcell',
@@ -102,7 +102,7 @@ class MGXS(object):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section
@@ -144,11 +144,11 @@ class MGXS(object):
 
     def __init__(self, domain=None, domain_type=None,
                  energy_groups=None, by_nuclide=False, name=''):
-
         self._name = ''
         self._rxn_type = None
         self._by_nuclide = None
         self._nuclides = None
+        self._estimator = 'tracklength'
         self._domain = None
         self._domain_type = None
         self._energy_groups = None
@@ -160,6 +160,7 @@ class MGXS(object):
         self._loaded_sp = False
         self._derived = False
         self._hdf5_key = None
+        self._valid_estimators = ESTIMATOR_TYPES
 
         self.name = name
         self.by_nuclide = by_nuclide
@@ -250,7 +251,7 @@ class MGXS(object):
 
     @property
     def estimator(self):
-        return 'tracklength'
+        return self._estimator
 
     @property
     def tallies(self):
@@ -368,6 +369,11 @@ class MGXS(object):
         cv.check_iterable_type('nuclides', nuclides, basestring)
         self._nuclides = nuclides
 
+    @estimator.setter
+    def estimator(self, estimator):
+        cv.check_value('estimator', estimator, self._valid_estimators)
+        self._estimator = estimator
+
     @domain.setter
     def domain(self, domain):
         cv.check_type('domain', domain, _DOMAINS)
@@ -710,11 +716,13 @@ class MGXS(object):
 
     def get_xs(self, groups='all', subdomains='all', nuclides='all',
                xs_type='macro', order_groups='increasing',
-               value='mean', **kwargs):
+               value='mean', squeeze=True, **kwargs):
         r"""Returns an array of multi-group cross sections.
 
-        This method constructs a 2D NumPy array for the requested multi-group
-        cross section data data for one or more energy groups and subdomains.
+        This method constructs a 3D NumPy array for the requested
+        multi-group cross section data for one or more subdomains
+        (1st dimension), energy groups (2nd dimension), and nuclides
+        (3rd dimension).
 
         Parameters
         ----------
@@ -736,6 +744,9 @@ class MGXS(object):
             Defaults to 'increasing'.
         value : {'mean', 'std_dev', 'rel_err'}
             A string for the type of value to return. Defaults to 'mean'.
+        squeeze : bool
+            A boolean representing whether to eliminate the extra dimensions
+            of the multi-dimensional array to be returned. Defaults to True.
 
         Returns
         -------
@@ -806,25 +817,29 @@ class MGXS(object):
                 xs /= densities[np.newaxis, :, np.newaxis]
                 xs[np.isnan(xs)] = 0.0
 
+        # Eliminate the trivial score dimension
+        xs = np.squeeze(xs, axis=len(xs.shape) - 1)
+        xs = np.nan_to_num(xs)
+
+        if groups == 'all':
+            num_groups = self.num_groups
+        else:
+            num_groups = len(groups)
+
+        # Reshape tally data array with separate axes for domain and energy
+        num_subdomains = int(xs.shape[0] / num_groups)
+        new_shape = (num_subdomains, num_groups) + xs.shape[1:]
+        xs = np.reshape(xs, new_shape)
+
         # Reverse data if user requested increasing energy groups since
         # tally data is stored in order of increasing energies
         if order_groups == 'increasing':
-            if groups == 'all':
-                num_groups = self.num_groups
-            else:
-                num_groups = len(groups)
-
-            # Reshape tally data array with separate axes for domain and energy
-            num_subdomains = int(xs.shape[0] / num_groups)
-            new_shape = (num_subdomains, num_groups) + xs.shape[1:]
-            xs = np.reshape(xs, new_shape)
-
-            # Reverse energies to align with increasing energy groups
             xs = xs[:, ::-1, :]
 
-        # Eliminate trivial dimensions
-        xs = np.squeeze(xs)
-        xs = np.atleast_1d(xs)
+        if squeeze:
+            xs = np.squeeze(xs)
+            xs = np.atleast_1d(xs)
+
         return xs
 
     def get_condensed_xs(self, coarse_groups):
@@ -1337,8 +1352,6 @@ class MGXS(object):
                 std_dev = self.get_xs(subdomains=[subdomain], nuclides=[nuclide],
                                       xs_type=xs_type, value='std_dev',
                                       row_column=row_column)
-                average = average.squeeze()
-                std_dev = std_dev.squeeze()
 
                 # Add MGXS results data to the HDF5 group
                 nuclide_group.require_dataset('average', dtype=np.float64,
@@ -1504,15 +1517,14 @@ class MGXS(object):
         if 'energy low [MeV]' in df and 'energyout low [MeV]' in df:
             df.rename(columns={'energy low [MeV]': 'group in'},
                       inplace=True)
-            in_groups = np.tile(all_groups, self.num_subdomains)
-            in_groups = np.repeat(in_groups, df.shape[0] / in_groups.size)
+            in_groups = np.tile(all_groups, int(self.num_subdomains))
+            in_groups = np.repeat(in_groups, int(df.shape[0] / in_groups.size))
             df['group in'] = in_groups
             del df['energy high [MeV]']
 
             df.rename(columns={'energyout low [MeV]': 'group out'},
                       inplace=True)
-            out_groups = np.repeat(all_groups, self.xs_tally.num_scores)
-            out_groups = np.tile(out_groups, df.shape[0] / out_groups.size)
+            out_groups = np.tile(all_groups, int(df.shape[0] / all_groups.size))
             df['group out'] = out_groups
             del df['energyout high [MeV]']
             columns = ['group in', 'group out']
@@ -1520,14 +1532,14 @@ class MGXS(object):
         elif 'energyout low [MeV]' in df:
             df.rename(columns={'energyout low [MeV]': 'group out'},
                       inplace=True)
-            in_groups = np.tile(all_groups, self.num_subdomains)
+            in_groups = np.tile(all_groups, int(df.shape[0] / all_groups.size))
             df['group out'] = in_groups
             del df['energyout high [MeV]']
             columns = ['group out']
 
         elif 'energy low [MeV]' in df:
             df.rename(columns={'energy low [MeV]': 'group in'}, inplace=True)
-            in_groups = np.tile(all_groups, self.num_subdomains)
+            in_groups = np.tile(all_groups, int(df.shape[0] / all_groups.size))
             df['group in'] = in_groups
             del df['energy high [MeV]']
             columns = ['group in']
@@ -1562,6 +1574,7 @@ class MGXS(object):
                                (mesh_str, 'z')] + columns, inplace=True)
         else:
             df.sort_values(by=[self.domain_type] + columns, inplace=True)
+
         return df
 
     def get_units(self, xs_type='macro'):
@@ -1636,7 +1649,7 @@ class MatrixMGXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section
@@ -1685,18 +1698,16 @@ class MatrixMGXS(MGXS):
 
         return [[energy], [energy, energyout]]
 
-    @property
-    def estimator(self):
-        return 'analog'
-
     def get_xs(self, in_groups='all', out_groups='all',
                subdomains='all', nuclides='all',
                xs_type='macro', order_groups='increasing',
-               row_column='inout', value='mean', **kwargs):
+               row_column='inout', value='mean', squeeze=True, **kwargs):
         """Returns an array of multi-group cross sections.
 
-        This method constructs a 2D NumPy array for the requested multi-group
-        matrix data for one or more energy groups and subdomains.
+        This method constructs a 4D NumPy array for the requested
+        multi-group cross section data for one or more subdomains
+        (1st dimension), energy groups in (2nd dimension), energy groups out
+        (3rd dimension), and nuclides (4th dimension).
 
         Parameters
         ----------
@@ -1725,6 +1736,9 @@ class MatrixMGXS(MGXS):
             Defaults to 'inout'.
         value : {'mean', 'std_dev', 'rel_err'}
             A string for the type of value to return. Defaults to 'mean'.
+        squeeze : bool
+            A boolean representing whether to eliminate the extra dimensions
+            of the multi-dimensional array to be returned. Defaults to True.
 
         Returns
         -------
@@ -1796,8 +1810,6 @@ class MatrixMGXS(MGXS):
                                           filter_bins=filter_bins,
                                           nuclides=query_nuclides, value=value)
 
-        xs = np.nan_to_num(xs)
-
         # Divide by atom number densities for microscopic cross sections
         if xs_type == 'micro':
             if self.by_nuclide:
@@ -1808,33 +1820,36 @@ class MatrixMGXS(MGXS):
                 xs /= densities[np.newaxis, :, np.newaxis]
                 xs[np.isnan(xs)] = 0.0
 
+        # Eliminate the trivial score dimension
+        xs = np.squeeze(xs, axis=len(xs.shape) - 1)
+        xs = np.nan_to_num(xs)
+
+        if in_groups == 'all':
+            num_in_groups = self.num_groups
+        else:
+            num_in_groups = len(in_groups)
+
+        if out_groups == 'all':
+            num_out_groups = self.num_groups
+        else:
+            num_out_groups = len(out_groups)
+
+        # Reshape tally data array with separate axes for domain and energy
+        num_subdomains = int(xs.shape[0] / (num_in_groups * num_out_groups))
+        new_shape = (num_subdomains, num_in_groups, num_out_groups)
+        new_shape += xs.shape[1:]
+        xs = np.reshape(xs, new_shape)
+
+        # Transpose the matrix if requested by user
+        if row_column == 'outin':
+            xs = np.swapaxes(xs, 1, 2)
+
         # Reverse data if user requested increasing energy groups since
         # tally data is stored in order of increasing energies
         if order_groups == 'increasing':
-            if in_groups == 'all':
-                num_in_groups = self.num_groups
-            else:
-                num_in_groups = len(in_groups)
-            if out_groups == 'all':
-                num_out_groups = self.num_groups
-            else:
-                num_out_groups = len(out_groups)
-
-            # Reshape tally data array with separate axes for domain and energy
-            num_subdomains = int(xs.shape[0] /
-                                 (num_in_groups * num_out_groups))
-            new_shape = (num_subdomains, num_in_groups, num_out_groups)
-            new_shape += xs.shape[1:]
-            xs = np.reshape(xs, new_shape)
-
-            # Transpose the matrix if requested by user
-            if row_column == 'outin':
-                xs = np.swapaxes(xs, 1, 2)
-
-            # Reverse energies to align with increasing energy groups
             xs = xs[:, ::-1, ::-1, :]
 
-            # Eliminate trivial dimensions
+        if squeeze:
             xs = np.squeeze(xs)
             xs = np.atleast_2d(xs)
 
@@ -2066,7 +2081,7 @@ class TotalXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -2184,7 +2199,7 @@ class TransportXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : 'analog'
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -2227,6 +2242,8 @@ class TransportXS(MGXS):
         super(TransportXS, self).__init__(domain, domain_type,
                                           groups, by_nuclide, name)
         self._rxn_type = 'transport'
+        self._estimator = 'analog'
+        self._valid_estimators = ['analog']
 
     @property
     def scores(self):
@@ -2239,10 +2256,6 @@ class TransportXS(MGXS):
         energyout_filter = openmc.Filter('energyout', group_edges)
         return [[energy_filter], [energy_filter], [energyout_filter]]
 
-    @property
-    def estimator(self):
-        return 'analog'
-
     @property
     def rxn_rate_tally(self):
         if self._rxn_rate_tally is None:
@@ -2314,7 +2327,7 @@ class NuTransportXS(TransportXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : 'analog'
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -2435,7 +2448,7 @@ class AbsorptionXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -2452,7 +2465,8 @@ class AbsorptionXS(MGXS):
         The number of subdomains is unity for 'material', 'cell' and 'universe'
         domain types. This is equal to the number of cell instances
         for 'distribcell' domain types (it is equal to unity prior to loading
-        tally data from a statepoint file).
+        tally data from a statepoint file) and the number of mesh cells for
+        'mesh' domain types.
     num_nuclides : int
         The number of nuclides for which the multi-group cross section is
         being tracked. This is unity if the by_nuclide attribute is False.
@@ -2551,7 +2565,7 @@ class CaptureXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -2673,7 +2687,7 @@ class FissionXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -2784,7 +2798,7 @@ class NuFissionXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -2828,7 +2842,6 @@ class NuFissionXS(MGXS):
                                           groups, by_nuclide, name)
         self._rxn_type = 'nu-fission'
 
-
 class KappaFissionXS(MGXS):
     r"""A recoverable fission energy production rate multi-group cross section.
 
@@ -2900,7 +2913,7 @@ class KappaFissionXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -3013,7 +3026,7 @@ class ScatterXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -3128,7 +3141,7 @@ class NuScatterXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -3171,10 +3184,8 @@ class NuScatterXS(MGXS):
         super(NuScatterXS, self).__init__(domain, domain_type,
                                           groups, by_nuclide, name)
         self._rxn_type = 'nu-scatter'
-
-    @property
-    def estimator(self):
-        return 'analog'
+        self._estimator = 'analog'
+        self._valid_estimators = ['analog']
 
 
 class ScatterMatrixXS(MatrixMGXS):
@@ -3262,7 +3273,7 @@ class ScatterMatrixXS(MatrixMGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : 'analog'
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -3308,6 +3319,8 @@ class ScatterMatrixXS(MatrixMGXS):
         self._correction = 'P0'
         self._legendre_order = 0
         self._hdf5_key = 'scatter matrix'
+        self._estimator = 'analog'
+        self._valid_estimators = ['analog']
 
     def __deepcopy__(self, memo):
         clone = super(ScatterMatrixXS, self).__deepcopy__(memo)
@@ -3511,11 +3524,13 @@ class ScatterMatrixXS(MatrixMGXS):
     def get_xs(self, in_groups='all', out_groups='all',
                subdomains='all', nuclides='all', moment='all',
                xs_type='macro', order_groups='increasing',
-               row_column='inout', value='mean'):
+               row_column='inout', value='mean', squeeze=True):
         r"""Returns an array of multi-group cross sections.
 
-        This method constructs a 2D NumPy array for the requested scattering
-        matrix data data for one or more energy groups and subdomains.
+        This method constructs a 5D NumPy array for the requested
+        multi-group cross section data for one or more subdomains
+        (1st dimension), energy groups in (2nd dimension), energy groups out
+        (3rd dimension), nuclides (4th dimension), and moments (5th dimension).
 
         NOTE: The scattering moments are not multiplied by the :math:`(2l+1)/2`
         prefactor in the expansion of the scattering source into Legendre
@@ -3551,6 +3566,9 @@ class ScatterMatrixXS(MatrixMGXS):
             Defaults to 'inout'.
         value : {'mean', 'std_dev', 'rel_err'}
             A string for the type of value to return. Defaults to 'mean'.
+        squeeze : bool
+            A boolean representing whether to eliminate the extra dimensions
+            of the multi-dimensional array to be returned. Defaults to True.
 
         Returns
         -------
@@ -3629,8 +3647,6 @@ class ScatterMatrixXS(MatrixMGXS):
                                           filter_bins=filter_bins,
                                           nuclides=query_nuclides, value=value)
 
-        xs = np.nan_to_num(xs)
-
         # Divide by atom number densities for microscopic cross sections
         if xs_type == 'micro':
             if self.by_nuclide:
@@ -3641,32 +3657,35 @@ class ScatterMatrixXS(MatrixMGXS):
                 xs /= densities[np.newaxis, :, np.newaxis]
                 xs[np.isnan(xs)] = 0.0
 
+        # Convert and nans to zero
+        xs = np.nan_to_num(xs)
+
+        if in_groups == 'all':
+            num_in_groups = self.num_groups
+        else:
+            num_in_groups = len(in_groups)
+
+        if out_groups == 'all':
+            num_out_groups = self.num_groups
+        else:
+            num_out_groups = len(out_groups)
+
+        # Reshape tally data array with separate axes for domain and energy
+        num_subdomains = int(xs.shape[0] / (num_in_groups * num_out_groups))
+        new_shape = (num_subdomains, num_in_groups, num_out_groups)
+        new_shape += xs.shape[1:]
+        xs = np.reshape(xs, new_shape)
+
+        # Transpose the scattering matrix if requested by user
+        if row_column == 'outin':
+            xs = np.swapaxes(xs, 1, 2)
+
         # Reverse data if user requested increasing energy groups since
         # tally data is stored in order of increasing energies
         if order_groups == 'increasing':
-            if in_groups == 'all':
-                num_in_groups = self.num_groups
-            else:
-                num_in_groups = len(in_groups)
-            if out_groups == 'all':
-                num_out_groups = self.num_groups
-            else:
-                num_out_groups = len(out_groups)
-
-            # Reshape tally data array with separate axes for domain and energy
-            num_subdomains = int(xs.shape[0] / (num_in_groups * num_out_groups))
-            new_shape = (num_subdomains, num_in_groups, num_out_groups)
-            new_shape += xs.shape[1:]
-            xs = np.reshape(xs, new_shape)
-
-            # Transpose the scattering matrix if requested by user
-            if row_column == 'outin':
-                xs = np.swapaxes(xs, 1, 2)
-
-            # Reverse energies to align with increasing energy groups
             xs = xs[:, ::-1, ::-1, :]
 
-            # Eliminate trivial dimensions
+        if squeeze:
             xs = np.squeeze(xs)
             xs = np.atleast_2d(xs)
 
@@ -3723,7 +3742,7 @@ class ScatterMatrixXS(MatrixMGXS):
         if self.legendre_order > 0:
             # Insert a column corresponding to the Legendre moments
             moments = ['P{}'.format(i) for i in range(self.legendre_order+1)]
-            moments = np.tile(moments, df.shape[0] / len(moments))
+            moments = np.tile(moments, int(df.shape[0] / len(moments)))
             df['moment'] = moments
 
             # Place the moment column before the mean column
@@ -3924,7 +3943,7 @@ class NuScatterMatrixXS(ScatterMatrixXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : 'analog'
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -4046,7 +4065,7 @@ class MultiplicityMatrixXS(MatrixMGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : 'analog'
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -4089,6 +4108,8 @@ class MultiplicityMatrixXS(MatrixMGXS):
         super(MultiplicityMatrixXS, self).__init__(domain, domain_type, groups,
                                                    by_nuclide, name)
         self._rxn_type = 'multiplicity matrix'
+        self._estimator = 'analog'
+        self._valid_estimators = ['analog']
 
     @property
     def scores(self):
@@ -4193,7 +4214,7 @@ class NuFissionMatrixXS(MatrixMGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : 'analog'
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -4237,6 +4258,8 @@ class NuFissionMatrixXS(MatrixMGXS):
                                                 groups, by_nuclide, name)
         self._rxn_type = 'nu-fission'
         self._hdf5_key = 'nu-fission matrix'
+        self._estimator = 'analog'
+        self._valid_estimators = ['analog']
 
 
 class Chi(MGXS):
@@ -4308,7 +4331,7 @@ class Chi(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : 'analog'
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -4350,6 +4373,8 @@ class Chi(MGXS):
                  groups=None, by_nuclide=False, name=''):
         super(Chi, self).__init__(domain, domain_type, groups, by_nuclide, name)
         self._rxn_type = 'chi'
+        self._estimator = 'analog'
+        self._valid_estimators = ['analog']
 
     @property
     def scores(self):
@@ -4367,10 +4392,6 @@ class Chi(MGXS):
     def tally_keys(self):
         return ['nu-fission-in', 'nu-fission-out']
 
-    @property
-    def estimator(self):
-        return 'analog'
-
     @property
     def rxn_rate_tally(self):
         if self._rxn_rate_tally is None:
@@ -4507,11 +4528,13 @@ class Chi(MGXS):
 
     def get_xs(self, groups='all', subdomains='all', nuclides='all',
                xs_type='macro', order_groups='increasing',
-               value='mean', **kwargs):
+               value='mean', squeeze=True, **kwargs):
         """Returns an array of the fission spectrum.
 
-        This method constructs a 2D NumPy array for the requested multi-group
-        cross section data data for one or more energy groups and subdomains.
+        This method constructs a 3D NumPy array for the requested
+        multi-group cross section data for one or more subdomains
+        (1st dimension), energy groups (2nd dimension), and nuclides
+        (3rd dimension).
 
         Parameters
         ----------
@@ -4533,6 +4556,9 @@ class Chi(MGXS):
             Defaults to 'increasing'.
         value : {'mean', 'std_dev', 'rel_err'}
             A string for the type of value to return. Defaults to 'mean'.
+        squeeze : bool
+            A boolean representing whether to eliminate the extra dimensions
+            of the multi-dimensional array to be returned. Defaults to True.
 
         Returns
         -------
@@ -4624,27 +4650,29 @@ class Chi(MGXS):
             xs = self.xs_tally.get_values(filters=filters,
                                           filter_bins=filter_bins, value=value)
 
+        # Eliminate the trivial score dimension
+        xs = np.squeeze(xs, axis=len(xs.shape) - 1)
+        xs = np.nan_to_num(xs)
+
+        # Reshape tally data array with separate axes for domain and energy
+        if groups == 'all':
+            num_groups = self.num_groups
+        else:
+            num_groups = len(groups)
+
+        num_subdomains = int(xs.shape[0] / num_groups)
+        new_shape = (num_subdomains, num_groups) + xs.shape[1:]
+        xs = np.reshape(xs, new_shape)
+
         # Reverse data if user requested increasing energy groups since
         # tally data is stored in order of increasing energies
         if order_groups == 'increasing':
-
-            # Reshape tally data array with separate axes for domain and energy
-            if groups == 'all':
-                num_groups = self.num_groups
-            else:
-                num_groups = len(groups)
-            num_subdomains = int(xs.shape[0] / num_groups)
-            new_shape = (num_subdomains, num_groups) + xs.shape[1:]
-            xs = np.reshape(xs, new_shape)
-
-            # Reverse energies to align with increasing energy groups
             xs = xs[:, ::-1, :]
 
-            # Eliminate trivial dimensions
+        if squeeze:
             xs = np.squeeze(xs)
             xs = np.atleast_1d(xs)
 
-        xs = np.nan_to_num(xs)
         return xs
 
     def get_pandas_dataframe(self, groups='all', nuclides='all',
@@ -4753,7 +4781,7 @@ class ChiPrompt(Chi):
 
        \langle \nu^p \sigma_{f,g' \rightarrow g} \phi \rangle &= \int_{r \in V}
        dr \int_{4\pi} d\Omega' \int_0^\infty dE' \int_{E_g}^{E_{g-1}} dE \;
-       \chi(E) \nu^p \sigma_f (r, E') \psi(r, E', \Omega')\\
+       \chi(E)^p \nu^p \sigma_f (r, E') \psi(r, E', \Omega')\\
        \langle \nu^p \sigma_f \phi \rangle &= \int_{r \in V} dr \int_{4\pi}
        d\Omega' \int_0^\infty dE' \int_0^\infty dE \; \chi(E) \nu^p \sigma_f (r,
        E') \psi(r, E', \Omega') \\
@@ -4798,7 +4826,7 @@ class ChiPrompt(Chi):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : 'analog'
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -4913,7 +4941,7 @@ class InverseVelocity(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -4930,7 +4958,8 @@ class InverseVelocity(MGXS):
         The number of subdomains is unity for 'material', 'cell' and 'universe'
         domain types. This is equal to the number of cell instances
         for 'distribcell' domain types (it is equal to unity prior to loading
-        tally data from a statepoint file).
+        tally data from a statepoint file) and the number of mesh cells for
+        'mesh' domain types.
     num_nuclides : int
         The number of nuclides for which the multi-group cross section is
         being tracked. This is unity if the by_nuclide attribute is False.
@@ -5047,7 +5076,7 @@ class PromptNuFissionXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys

openmc/statepoint.py

@@ -701,7 +701,7 @@ class StatePoint(object):
                 if tally_filter.type == 'surface':
                     surface_ids = []
                     for bin in tally_filter.bins:
-                        surface_ids.append(summary.surfaces[bin].id)
+                        surface_ids.append(bin)
                     tally_filter.bins = surface_ids
 
                 if tally_filter.type in ['cell', 'distribcell']:

openmc/tallies.py

@@ -40,6 +40,9 @@ _SCORE_CLASSES = (basestring, CrossScore, AggregateScore)
 _NUCLIDE_CLASSES = (basestring, Nuclide, CrossNuclide, AggregateNuclide)
 _FILTER_CLASSES = (Filter, CrossFilter, AggregateFilter)
 
+# Valid types of estimators
+ESTIMATOR_TYPES = ['tracklength', 'collision', 'analog']
+
 
 def reset_auto_tally_id():
     """Reset counter for auto-generated tally IDs."""
@@ -387,8 +390,7 @@ class Tally(object):
 
     @estimator.setter
     def estimator(self, estimator):
-        cv.check_value('estimator', estimator,
-                       ['analog', 'tracklength', 'collision'])
+        cv.check_value('estimator', estimator, ESTIMATOR_TYPES)
         self._estimator = estimator
 
     @triggers.setter
@@ -795,6 +797,9 @@ class Tally(object):
             else:
                 no_scores_match = False
 
+            if score == 'current' and score not in self.scores:
+                return False
+
         # Nuclides cannot be specified on 'flux' scores
         if 'flux' in self.scores or 'flux' in other.scores:
             if self.nuclides != other.nuclides:
@@ -2197,8 +2202,8 @@ class Tally(object):
 
         """
 
-        cv.check_type('filter1', filter1, (Filter, CrossFilter, AggregateFilter))
-        cv.check_type('filter2', filter2, (Filter, CrossFilter, AggregateFilter))
+        cv.check_type('filter1', filter1, _FILTER_CLASSES)
+        cv.check_type('filter2', filter2, _FILTER_CLASSES)
 
         # Check that the filters exist in the tally and are not the same
         if filter1 == filter2:
@@ -2280,8 +2285,8 @@ class Tally(object):
                   'since it does not contain any results.'.format(self.id)
             raise ValueError(msg)
 
-        cv.check_type('nuclide1', nuclide1, Nuclide)
-        cv.check_type('nuclide2', nuclide2, Nuclide)
+        cv.check_type('nuclide1', nuclide1, _NUCLIDE_CLASSES)
+        cv.check_type('nuclide2', nuclide2, _NUCLIDE_CLASSES)
 
         # Check that the nuclides exist in the tally and are not the same
         if nuclide1 == nuclide2:
@@ -3318,7 +3323,7 @@ class Tally(object):
 
         """
 
-        cv.check_type('new_filter', new_filter, Filter)
+        cv.check_type('new_filter', new_filter, _FILTER_CLASSES)
 
         if new_filter in self.filters:
             msg = 'Unable to diagonalize Tally ID="{0}" which already ' \

src/cmfd_data.F90

@@ -51,9 +51,9 @@ contains
   subroutine compute_xs()
 
     use constants,    only: FILTER_MESH, FILTER_ENERGYIN, FILTER_ENERGYOUT,    &
-                           FILTER_SURFACE, IN_RIGHT, OUT_RIGHT, IN_FRONT,      &
-                           OUT_FRONT, IN_TOP, OUT_TOP, CMFD_NOACCEL, ZERO,     &
-                           ONE, TINY_BIT
+                           FILTER_SURFACE, OUT_LEFT, OUT_RIGHT, OUT_BACK,      &
+                           OUT_FRONT, OUT_BOTTOM, OUT_TOP, CMFD_NOACCEL,       &
+                           ZERO, ONE, TINY_BIT
     use error,        only: fatal_error
     use global,       only: cmfd, n_cmfd_tallies, cmfd_tallies, meshes,&
                            matching_bins
@@ -236,23 +236,33 @@ contains
 
                 ! Left surface
                 matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
-                     (/ i-1, j, k /) + 1, .true.)
-                matching_bins(i_filter_surf) = IN_RIGHT
+                     (/ i, j, k /))
+                matching_bins(i_filter_surf) = OUT_LEFT
                 score_index = sum((matching_bins(1:size(t % filters)) - 1) &
                      * t%stride) + 1 ! outgoing
                 cmfd % current(1,h,i,j,k) = t % results(1,score_index) % sum
-                matching_bins(i_filter_surf) = OUT_RIGHT
-                score_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                     * t % stride) + 1 ! incoming
-                cmfd % current(2,h,i,j,k) = t % results(1,score_index) % sum
+
+                if (i > 1) then
+                  matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
+                       (/ i-1, j, k /))
+                  matching_bins(i_filter_surf) = OUT_RIGHT
+                  score_index = sum((matching_bins(1:size(t % filters)) - 1) &
+                       * t % stride) + 1 ! incoming
+                  cmfd % current(2,h,i,j,k) = t % results(1,score_index) % sum
+                end if
 
                 ! Right surface
+                if (i < nx) then
+                  matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
+                       (/ i+1, j, k /) )
+                  matching_bins(i_filter_surf) = OUT_LEFT
+                  score_index = sum((matching_bins(1:size(t % filters)) - 1) &
+                       * t % stride) + 1 ! incoming
+                  cmfd % current(3,h,i,j,k) = t % results(1,score_index) % sum
+                end if
+
                 matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
-                     (/ i, j, k /) + 1, .true.)
-                matching_bins(i_filter_surf) = IN_RIGHT
-                score_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                     * t % stride) + 1 ! incoming
-                cmfd % current(3,h,i,j,k) = t % results(1,score_index) % sum
+                     (/ i, j, k /) )
                 matching_bins(i_filter_surf) = OUT_RIGHT
                 score_index = sum((matching_bins(1:size(t % filters)) - 1) &
                      * t % stride) + 1 ! outgoing
@@ -260,23 +270,33 @@ contains
 
                 ! Back surface
                 matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
-                     (/ i, j-1, k /) + 1, .true.)
-                matching_bins(i_filter_surf) = IN_FRONT
+                     (/ i, j, k /))
+                matching_bins(i_filter_surf) = OUT_BACK
                 score_index = sum((matching_bins(1:size(t % filters)) - 1) &
                      * t % stride) + 1 ! outgoing
                 cmfd % current(5,h,i,j,k) = t % results(1,score_index) % sum
-                matching_bins(i_filter_surf) = OUT_FRONT
-                score_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                     * t % stride) + 1 ! incoming
-                cmfd % current(6,h,i,j,k) = t % results(1,score_index) % sum
+
+                if (j > 1) then
+                  matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
+                       (/ i, j-1, k /))
+                  matching_bins(i_filter_surf) = OUT_FRONT
+                  score_index = sum((matching_bins(1:size(t % filters)) - 1) &
+                       * t % stride) + 1 ! incoming
+                  cmfd % current(6,h,i,j,k) = t % results(1,score_index) % sum
+                end if
 
                 ! Front surface
+                if (j < ny) then
+                  matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
+                       (/ i, j+1, k /))
+                  matching_bins(i_filter_surf) = OUT_BACK
+                  score_index = sum((matching_bins(1:size(t % filters)) - 1) &
+                       * t % stride) + 1 ! incoming
+                  cmfd % current(7,h,i,j,k) = t % results(1,score_index) % sum
+                end if
+
                 matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
-                     (/ i, j, k /) + 1, .true.)
-                matching_bins(i_filter_surf) = IN_FRONT
-                score_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                     * t % stride) + 1 ! incoming
-                cmfd % current(7,h,i,j,k) = t % results(1,score_index) % sum
+                     (/ i, j, k /))
                 matching_bins(i_filter_surf) = OUT_FRONT
                 score_index = sum((matching_bins(1:size(t % filters)) - 1) &
                      * t % stride) + 1 ! outgoing
@@ -284,23 +304,33 @@ contains
 
                 ! Bottom surface
                 matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
-                     (/ i, j, k-1 /) + 1, .true.)
-                matching_bins(i_filter_surf) = IN_TOP
+                     (/ i, j, k /))
+                matching_bins(i_filter_surf) = OUT_BOTTOM
                 score_index = sum((matching_bins(1:size(t % filters)) - 1) &
                      * t % stride) + 1 ! outgoing
                 cmfd % current(9,h,i,j,k) = t % results(1,score_index) % sum
-                matching_bins(i_filter_surf) = OUT_TOP
-                score_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                     * t % stride) + 1 ! incoming
-                cmfd % current(10,h,i,j,k) = t % results(1,score_index) % sum
+
+                if (k > 1) then
+                  matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
+                       (/ i, j, k-1 /))
+                  matching_bins(i_filter_surf) = OUT_TOP
+                  score_index = sum((matching_bins(1:size(t % filters)) - 1) &
+                       * t % stride) + 1 ! incoming
+                  cmfd % current(10,h,i,j,k) = t % results(1,score_index) % sum
+                end if
 
                 ! Top surface
+                if (k < nz) then
+                  matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
+                       (/ i, j, k+1 /))
+                  matching_bins(i_filter_surf) = OUT_BOTTOM
+                  score_index = sum((matching_bins(1:size(t % filters)) - 1) &
+                       * t % stride) + 1 ! incoming
+                  cmfd % current(11,h,i,j,k) = t % results(1,score_index) % sum
+                end if
+
                 matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
-                     (/ i, j, k /) + 1, .true.)
-                matching_bins(i_filter_surf) = IN_TOP
-                score_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                     * t % stride) + 1 ! incoming
-                cmfd % current(11,h,i,j,k) = t % results(1,score_index) % sum
+                     (/ i, j, k /))
                 matching_bins(i_filter_surf) = OUT_TOP
                 score_index = sum((matching_bins(1:size(t % filters)) - 1) &
                      * t % stride) + 1 ! outgoing

src/cmfd_input.F90

@@ -534,10 +534,10 @@ contains
           filt % n_bins = 2 * m % n_dimension
           allocate(filt % surfaces(2 * m % n_dimension))
           if (m % n_dimension == 2) then
-            filt % surfaces = (/ IN_RIGHT, OUT_RIGHT, IN_FRONT, OUT_FRONT /)
+            filt % surfaces = (/ OUT_LEFT, OUT_RIGHT, OUT_BACK, OUT_FRONT /)
           elseif (m % n_dimension == 3) then
-            filt % surfaces = (/ IN_RIGHT, OUT_RIGHT, IN_FRONT, OUT_FRONT, &
-                 IN_TOP, OUT_TOP /)
+            filt % surfaces = (/ OUT_LEFT, OUT_RIGHT, OUT_BACK, OUT_FRONT, &
+                 OUT_BOTTOM, OUT_TOP /)
           end if
         end select
         t % find_filter(FILTER_SURFACE) = n_filters

src/constants.F90

@@ -359,12 +359,12 @@ module constants
 
   ! Tally surface current directions
   integer, parameter :: &
-       IN_RIGHT  = 1,   &
-       OUT_RIGHT = 2,   &
-       IN_FRONT  = 3,   &
-       OUT_FRONT = 4,   &
-       IN_TOP    = 5,   &
-       OUT_TOP   = 6
+       OUT_LEFT   = 1,   &   ! x min
+       OUT_RIGHT  = 2,   &   ! x max
+       OUT_BACK   = 3,   &   ! y min
+       OUT_FRONT  = 4,   &   ! y max
+       OUT_BOTTOM = 5,   &   ! z min
+       OUT_TOP    = 6        ! z max
 
   ! Tally trigger types and threshold
   integer, parameter :: &

src/input_xml.F90

@@ -3047,18 +3047,18 @@ contains
                    // " specified on tally " // trim(to_str(t % id)))
             end if
 
-            ! Determine number of bins -- this is assuming that the tally is
-            ! a volume tally and not a surface current tally. If it is a
-            ! surface current tally, the number of bins will get reset later
+            ! Determine number of bins
             filt % n_bins = product(m % dimension)
 
             ! Store the index of the mesh
             filt % mesh = i_mesh
           end select
+
           ! Set the filter index in the tally find_filter array
           t % find_filter(FILTER_MESH) = j
 
         case ('energy')
+
           ! Allocate and declare the filter type
           allocate(EnergyFilter::t % filters(j) % obj)
           select type (filt => t % filters(j) % obj)
@@ -3676,10 +3676,6 @@ contains
                    &same tally as surface currents")
             end if
 
-            ! Since the number of bins for the mesh filter was already set
-            ! assuming it was a volume tally, we need to adjust the number
-            ! of bins
-
             ! Get index of mesh filter
             k = t % find_filter(FILTER_MESH)
 
@@ -3689,19 +3685,6 @@ contains
                    &filter.")
             end if
 
-            ! Declare the type of the mesh filter
-            select type(filt => t % filters(k) % obj)
-            type is (MeshFilter)
-
-              ! Get pointer to mesh
-              i_mesh = filt % mesh
-              m => meshes(i_mesh)
-
-              ! We need to increase the dimension by one since we also need
-              ! currents coming into and out of the boundary mesh cells.
-              filt % n_bins = product(m % dimension + 1)
-            end select
-
             ! Copy filters to temporary array
             allocate(filters(size(t % filters) + 1))
             filters(1:size(t % filters)) = t % filters
@@ -3718,10 +3701,10 @@ contains
               filt % n_bins = 2 * m % n_dimension
               allocate(filt % surfaces(2 * m % n_dimension))
               if (m % n_dimension == 2) then
-                filt % surfaces = (/ IN_RIGHT, OUT_RIGHT, IN_FRONT, OUT_FRONT /)
+                filt % surfaces = (/ OUT_LEFT, OUT_RIGHT, OUT_BACK, OUT_FRONT /)
               elseif (m % n_dimension == 3) then
-                filt % surfaces = (/ IN_RIGHT,  OUT_RIGHT, IN_FRONT, OUT_FRONT,&
-                     IN_TOP, OUT_TOP /)
+                filt % surfaces = (/ OUT_LEFT,  OUT_RIGHT, OUT_BACK, OUT_FRONT,&
+                     OUT_BOTTOM, OUT_TOP /)
               end if
             end select
             t % find_filter(FILTER_SURFACE) = size(t % filters)

src/mesh.F90

@@ -93,30 +93,21 @@ contains
 ! use in a TallyObject results array
 !===============================================================================
 
-  pure function mesh_indices_to_bin(m, ijk, surface_current) result(bin)
+  pure function mesh_indices_to_bin(m, ijk) result(bin)
     type(RegularMesh), intent(in) :: m
     integer, intent(in)           :: ijk(:)
-    logical, intent(in), optional :: surface_current
     integer                       :: bin
 
+    integer :: n_x ! number of mesh cells in x direction
     integer :: n_y ! number of mesh cells in y direction
-    integer :: n_z ! number of mesh cells in z direction
 
-    if (present(surface_current)) then
-      n_y = m % dimension(2) + 1
-    else
-      n_y = m % dimension(2)
-    end if
+    n_x = m % dimension(1)
+    n_y = m % dimension(2)
 
     if (m % n_dimension == 2) then
-      bin = (ijk(1) - 1)*n_y + ijk(2)
+      bin = (ijk(2) - 1)*n_x + ijk(1)
     elseif (m % n_dimension == 3) then
-      if (present(surface_current)) then
-        n_z = m % dimension(3) + 1
-      else
-        n_z = m % dimension(3)
-      end if
-      bin = (ijk(1) - 1)*n_y*n_z + (ijk(2) - 1)*n_z + ijk(3)
+      bin = (ijk(3) - 1)*n_y*n_x + (ijk(2) - 1)*n_x + ijk(1)
     end if
 
   end function mesh_indices_to_bin
@@ -131,19 +122,19 @@ contains
     integer, intent(in)           :: bin
     integer, intent(out)          :: ijk(:)
 
+    integer :: n_x ! number of mesh cells in x direction
     integer :: n_y ! number of mesh cells in y direction
-    integer :: n_z ! number of mesh cells in z direction
 
+    n_x = m % dimension(1)
     n_y = m % dimension(2)
 
     if (m % n_dimension == 2) then
-      ijk(1) = (bin - 1)/n_y + 1
-      ijk(2) = mod(bin - 1, n_y) + 1
+      ijk(1) = mod(bin - 1, n_x) + 1
+      ijk(2) = (bin - 1)/n_x + 1
     else if (m % n_dimension == 3) then
-      n_z = m % dimension(3)
-      ijk(1) = (bin - 1)/(n_y*n_z) + 1
-      ijk(2) = mod(bin - 1, n_y*n_z)/n_z + 1
-      ijk(3) = mod(bin - 1, n_z) + 1
+      ijk(1) = mod(bin - 1, n_x) + 1
+      ijk(2) = mod(bin - 1, n_x*n_y)/n_x + 1
+      ijk(3) = (bin - 1)/(n_x*n_y) + 1
     end if
 
   end subroutine bin_to_mesh_indices

src/output.F90

@@ -1036,8 +1036,8 @@ contains
 
             ! Left Surface
             matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i-1, j, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_RIGHT
+                 mesh_indices_to_bin(m, (/ i, j, k /))
+            matching_bins(i_filter_surf) = OUT_LEFT
             filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                  * t % stride) + 1
             write(UNIT=unit_tally, FMT='(5X,A,T35,A,"+/- ",A)') &
@@ -1045,25 +1045,9 @@ contains
                  to_str(t % results(1,filter_index) % sum), &
                  trim(to_str(t % results(1,filter_index) % sum_sq))
 
-            matching_bins(i_filter_surf) = OUT_RIGHT
-            filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                 * t % stride) + 1
-            write(UNIT=unit_tally, FMT='(5X,A,T35,A,"+/- ",A)') &
-                 "Incoming Current from Left", &
-                 to_str(t % results(1,filter_index) % sum), &
-                 trim(to_str(t % results(1,filter_index) % sum_sq))
-
             ! Right Surface
             matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_RIGHT
-            filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                 * t % stride) + 1
-            write(UNIT=unit_tally, FMT='(5X,A,T35,A,"+/- ",A)') &
-                 "Incoming Current from Right", &
-                 to_str(t % results(1,filter_index) % sum), &
-                 trim(to_str(t % results(1,filter_index) % sum_sq))
-
+                 mesh_indices_to_bin(m, (/ i, j, k /))
             matching_bins(i_filter_surf) = OUT_RIGHT
             filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                  * t % stride) + 1
@@ -1074,8 +1058,8 @@ contains
 
             ! Back Surface
             matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j-1, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_FRONT
+                 mesh_indices_to_bin(m, (/ i, j, k /))
+            matching_bins(i_filter_surf) = OUT_BACK
             filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                  * t % stride) + 1
             write(UNIT=unit_tally, FMT='(5X,A,T35,A,"+/- ",A)') &
@@ -1083,25 +1067,9 @@ contains
                  to_str(t % results(1,filter_index) % sum), &
                  trim(to_str(t % results(1,filter_index) % sum_sq))
 
-            matching_bins(i_filter_surf) = OUT_FRONT
-            filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                 * t % stride) + 1
-            write(UNIT=unit_tally, FMT='(5X,A,T35,A,"+/- ",A)') &
-                 "Incoming Current from Back", &
-                 to_str(t % results(1,filter_index) % sum), &
-                 trim(to_str(t % results(1,filter_index) % sum_sq))
-
             ! Front Surface
             matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_FRONT
-            filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                 * t % stride) + 1
-            write(UNIT=unit_tally, FMT='(5X,A,T35,A,"+/- ",A)') &
-                 "Incoming Current from Front", &
-                 to_str(t % results(1,filter_index) % sum), &
-                 trim(to_str(t % results(1,filter_index) % sum_sq))
-
+                 mesh_indices_to_bin(m, (/ i, j, k /))
             matching_bins(i_filter_surf) = OUT_FRONT
             filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                  * t % stride) + 1
@@ -1112,8 +1080,8 @@ contains
 
             ! Bottom Surface
             matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j, k-1 /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_TOP
+                 mesh_indices_to_bin(m, (/ i, j, k /))
+            matching_bins(i_filter_surf) = OUT_BOTTOM
             filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                  * t % stride) + 1
             write(UNIT=unit_tally, FMT='(5X,A,T35,A,"+/- ",A)') &
@@ -1121,25 +1089,9 @@ contains
                  to_str(t % results(1,filter_index) % sum), &
                  trim(to_str(t % results(1,filter_index) % sum_sq))
 
-            matching_bins(i_filter_surf) = OUT_TOP
-            filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                 * t % stride) + 1
-            write(UNIT=unit_tally, FMT='(5X,A,T35,A,"+/- ",A)') &
-                 "Incoming Current from Bottom", &
-                 to_str(t % results(1,filter_index) % sum), &
-                 trim(to_str(t % results(1,filter_index) % sum_sq))
-
             ! Top Surface
             matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_TOP
-            filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                 * t % stride) + 1
-            write(UNIT=unit_tally, FMT='(5X,A,T35,A,"+/- ",A)') &
-                 "Incoming Current from Top", &
-                 to_str(t % results(1,filter_index) % sum), &
-                 trim(to_str(t % results(1,filter_index) % sum_sq))
-
+                 mesh_indices_to_bin(m, (/ i, j, k /))
             matching_bins(i_filter_surf) = OUT_TOP
             filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                  * t % stride) + 1

src/tally.F90

@@ -2327,6 +2327,7 @@ contains
     integer :: filter_index         ! index of scoring bin
     integer :: i_filter_mesh        ! index of mesh filter in filters array
     integer :: i_filter_surf        ! index of surface filter in filters
+    integer :: i_filter_energy      ! index of energy filter in filters
     real(8) :: uvw(3)               ! cosine of angle of particle
     real(8) :: xyz0(3)              ! starting/intermediate coordinates
     real(8) :: xyz1(3)              ! ending coordinates of particle
@@ -2351,9 +2352,10 @@ contains
       i_tally = active_current_tallies % get_item(i)
       t => tallies(i_tally)
 
-      ! Get index for mesh and surface filters
+      ! Get index for mesh, surface, and energy filters
       i_filter_mesh = t % find_filter(FILTER_MESH)
       i_filter_surf = t % find_filter(FILTER_SURFACE)
+      i_filter_energy = t % find_filter(FILTER_ENERGYIN)
 
       ! Get pointer to mesh
       select type(filt => t % filters(i_filter_mesh) % obj)
@@ -2386,11 +2388,11 @@ contains
 
       ! Determine incoming energy bin.  We need to tell the energy filter this
       ! is a tracklength tally so it uses the pre-collision energy.
-      j = t % find_filter(FILTER_ENERGYIN)
-      if (j > 0) then
-        call t % filters(i) % obj % get_next_bin(p, ESTIMATOR_TRACKLENGTH, &
-             & NO_BIN_FOUND, matching_bins(j), filt_score)
-        if (matching_bins(j) == NO_BIN_FOUND) cycle
+      if (i_filter_energy > 0) then
+        call t % filters(i_filter_energy) % obj % get_next_bin(p, &
+             ESTIMATOR_TRACKLENGTH, NO_BIN_FOUND, &
+             matching_bins(i_filter_energy), filt_score)
+        if (matching_bins(i_filter_energy) == NO_BIN_FOUND) cycle
       end if
 
       ! =======================================================================
@@ -2405,10 +2407,10 @@ contains
         if (uvw(3) > 0) then
           do j = ijk0(3), ijk1(3) - 1
             ijk0(3) = j
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
               matching_bins(i_filter_surf) = OUT_TOP
               matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
+                   mesh_indices_to_bin(m, ijk0)
               filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                    * t % stride) + 1
 !$omp atomic
@@ -2417,12 +2419,12 @@ contains
             end if
           end do
         else
-          do j = ijk0(3) - 1, ijk1(3), -1
+          do j = ijk0(3), ijk1(3) + 1, -1
             ijk0(3) = j
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
-              matching_bins(i_filter_surf) = IN_TOP
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
+              matching_bins(i_filter_surf) = OUT_BOTTOM
               matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
+                   mesh_indices_to_bin(m, ijk0)
               filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                    * t % stride) + 1
 !$omp atomic
@@ -2437,10 +2439,10 @@ contains
         if (uvw(2) > 0) then
           do j = ijk0(2), ijk1(2) - 1
             ijk0(2) = j
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
               matching_bins(i_filter_surf) = OUT_FRONT
               matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
+                   mesh_indices_to_bin(m, ijk0)
               filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                    * t % stride) + 1
 !$omp atomic
@@ -2449,12 +2451,12 @@ contains
             end if
           end do
         else
-          do j = ijk0(2) - 1, ijk1(2), -1
+          do j = ijk0(2), ijk1(2) + 1, -1
             ijk0(2) = j
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
-              matching_bins(i_filter_surf) = IN_FRONT
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
+              matching_bins(i_filter_surf) = OUT_BACK
               matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
+                   mesh_indices_to_bin(m, ijk0)
               filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                    * t % stride) + 1
 !$omp atomic
@@ -2469,10 +2471,10 @@ contains
         if (uvw(1) > 0) then
           do j = ijk0(1), ijk1(1) - 1
             ijk0(1) = j
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
               matching_bins(i_filter_surf) = OUT_RIGHT
               matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
+                   mesh_indices_to_bin(m, ijk0)
               filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                    * t % stride) + 1
 !$omp atomic
@@ -2481,12 +2483,12 @@ contains
             end if
           end do
         else
-          do j = ijk0(1) - 1, ijk1(1), -1
+          do j = ijk0(1), ijk1(1) + 1, -1
             ijk0(1) = j
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
-              matching_bins(i_filter_surf) = IN_RIGHT
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
+              matching_bins(i_filter_surf) = OUT_LEFT
               matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
+                   mesh_indices_to_bin(m, ijk0)
               filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                    * t % stride) + 1
 !$omp atomic
@@ -2538,67 +2540,67 @@ contains
           if (uvw(1) > 0) then
             ! Crossing into right mesh cell -- this is treated as outgoing
             ! current from (i,j,k)
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
               matching_bins(i_filter_surf) = OUT_RIGHT
               matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
+                   mesh_indices_to_bin(m, ijk0)
             end if
             ijk0(1) = ijk0(1) + 1
             xyz_cross(1) = xyz_cross(1) + m % width(1)
           else
-            ! Crossing into left mesh cell -- this is treated as incoming
-            ! current in (i-1,j,k)
+            ! Crossing into left mesh cell -- this is treated as outgoing
+            ! current in (i,j,k)
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
+              matching_bins(i_filter_surf) = OUT_LEFT
+              matching_bins(i_filter_mesh) = &
+                   mesh_indices_to_bin(m, ijk0)
+            end if
             ijk0(1) = ijk0(1) - 1
             xyz_cross(1) = xyz_cross(1) - m % width(1)
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
-              matching_bins(i_filter_surf) = IN_RIGHT
-              matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
-            end if
           end if
         elseif (distance == d(2)) then
           if (uvw(2) > 0) then
             ! Crossing into front mesh cell -- this is treated as outgoing
             ! current in (i,j,k)
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
               matching_bins(i_filter_surf) = OUT_FRONT
               matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
+                   mesh_indices_to_bin(m, ijk0)
             end if
             ijk0(2) = ijk0(2) + 1
             xyz_cross(2) = xyz_cross(2) + m % width(2)
           else
-            ! Crossing into back mesh cell -- this is treated as incoming
-            ! current in (i,j-1,k)
+            ! Crossing into back mesh cell -- this is treated as outgoing
+            ! current in (i,j,k)
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
+              matching_bins(i_filter_surf) = OUT_BACK
+              matching_bins(i_filter_mesh) = &
+                   mesh_indices_to_bin(m, ijk0)
+            end if
             ijk0(2) = ijk0(2) - 1
             xyz_cross(2) = xyz_cross(2) - m % width(2)
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
-              matching_bins(i_filter_surf) = IN_FRONT
-              matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
-            end if
           end if
         else if (distance == d(3)) then
           if (uvw(3) > 0) then
             ! Crossing into top mesh cell -- this is treated as outgoing
             ! current in (i,j,k)
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
               matching_bins(i_filter_surf) = OUT_TOP
               matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
+                   mesh_indices_to_bin(m, ijk0)
             end if
             ijk0(3) = ijk0(3) + 1
             xyz_cross(3) = xyz_cross(3) + m % width(3)
           else
-            ! Crossing into bottom mesh cell -- this is treated as incoming
-            ! current in (i,j,k-1)
+            ! Crossing into bottom mesh cell -- this is treated as outgoing
+            ! current in (i,j,k)
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
+              matching_bins(i_filter_surf) = OUT_BOTTOM
+              matching_bins(i_filter_mesh) = &
+                   mesh_indices_to_bin(m, ijk0)
+            end if
             ijk0(3) = ijk0(3) - 1
             xyz_cross(3) = xyz_cross(3) - m % width(3)
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
-              matching_bins(i_filter_surf) = IN_TOP
-              matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
-            end if
           end if
         end if
 

src/trigger.F90

@@ -328,10 +328,11 @@ contains
               matching_bins(i_filter_ein) = l
             end if
 
-            ! Left Surface
             matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i-1, j, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_RIGHT
+                 mesh_indices_to_bin(m, (/ i, j, k /))
+
+            ! Left Surface
+            matching_bins(i_filter_surf) = OUT_LEFT
             filter_index = &
                  sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
             call get_trigger_uncertainty(std_dev, rel_err, 1, filter_index, t)
@@ -343,33 +344,7 @@ contains
             end if
             trigger % variance = std_dev**2
 
-            matching_bins(i_filter_surf) = OUT_RIGHT
-            filter_index = &
-                 sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
-            call get_trigger_uncertainty(std_dev, rel_err, 1, filter_index, t)
-            if (trigger % std_dev < std_dev) then
-              trigger % std_dev = std_dev
-            end if
-            if (trigger % rel_err < rel_err) then
-              trigger % rel_err = rel_err
-            end if
-            trigger % variance = trigger % std_dev**2
-
             ! Right Surface
-            matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_RIGHT
-            filter_index = &
-                 sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
-            call get_trigger_uncertainty(std_dev, rel_err, 1, filter_index, t)
-            if (trigger % std_dev < std_dev) then
-              trigger % std_dev = std_dev
-            end if
-            if (trigger % rel_err < rel_err) then
-              trigger % rel_err = rel_err
-            end if
-            trigger % variance = trigger % std_dev**2
-
             matching_bins(i_filter_surf) = OUT_RIGHT
             filter_index = &
                  sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
@@ -383,22 +358,7 @@ contains
             trigger % variance = trigger % std_dev**2
 
             ! Back Surface
-            matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j-1, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_FRONT
-            filter_index = &
-                 sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
-            call get_trigger_uncertainty(std_dev, rel_err, 1, filter_index, t)
-            if (trigger % std_dev < std_dev) then
-              trigger % std_dev = std_dev
-            end if
-            if (trigger % rel_err < rel_err) then
-              trigger % rel_err = rel_err
-            end if
-            trigger % variance = trigger % std_dev**2
-
-
-            matching_bins(i_filter_surf) = OUT_FRONT
+            matching_bins(i_filter_surf) = OUT_BACK
             filter_index = &
                  sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
             call get_trigger_uncertainty(std_dev, rel_err, 1, filter_index, t)
@@ -411,20 +371,6 @@ contains
             trigger % variance = trigger % std_dev**2
 
             ! Front Surface
-            matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_FRONT
-            filter_index = &
-                 sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
-            call get_trigger_uncertainty(std_dev, rel_err, 1, filter_index, t)
-            if (trigger % std_dev < std_dev) then
-              trigger % std_dev = std_dev
-            end if
-            if (trigger % rel_err < rel_err) then
-              trigger % rel_err = rel_err
-            end if
-            trigger % variance = trigger % std_dev**2
-
             matching_bins(i_filter_surf) = OUT_FRONT
             filter_index = &
                  sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
@@ -438,21 +384,7 @@ contains
             trigger % variance = trigger % std_dev**2
 
             ! Bottom Surface
-            matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j, k-1 /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_TOP
-            filter_index = &
-                 sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
-            call get_trigger_uncertainty(std_dev, rel_err, 1, filter_index, t)
-            if (trigger % std_dev < std_dev) then
-              trigger % std_dev = std_dev
-            end if
-            if (trigger % rel_err < rel_err) then
-              trigger % rel_err = rel_err
-            end if
-            trigger % variance = trigger % std_dev**2
-
-            matching_bins(i_filter_surf) = OUT_TOP
+            matching_bins(i_filter_surf) = OUT_BOTTOM
             filter_index = &
                  sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
             call get_trigger_uncertainty(std_dev, rel_err, 1, filter_index, t)
@@ -465,20 +397,6 @@ contains
             trigger % variance = trigger % std_dev**2
 
             ! Top Surface
-            matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_TOP
-            filter_index = &
-                 sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
-            call get_trigger_uncertainty(std_dev, rel_err, 1, filter_index, t)
-            if (trigger % std_dev < std_dev) then
-              trigger % std_dev = std_dev
-            end if
-            if (trigger % rel_err < rel_err) then
-              trigger % rel_err = rel_err
-            end if
-            trigger % variance = trigger % std_dev**2
-
             matching_bins(i_filter_surf) = OUT_TOP
             filter_index = &
                  sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1

tests/input_set.py

@@ -2,6 +2,7 @@ import openmc
 from openmc.source import Source
 from openmc.stats import Box
 
+import numpy as np
 
 class InputSet(object):
     def __init__(self):
@@ -673,6 +674,158 @@ class PinCellInputSet(object):
         self.plots.add_plot(plot)
 
 
+class AssemblyInputSet(object):
+    def __init__(self):
+        self.settings = openmc.Settings()
+        self.materials = openmc.Materials()
+        self.geometry = openmc.Geometry()
+        self.tallies = None
+        self.plots = None
+
+    def export(self):
+        self.settings.export_to_xml()
+        self.materials.export_to_xml()
+        self.geometry.export_to_xml()
+        if self.tallies is not None:
+            self.tallies.export_to_xml()
+        if self.plots is not None:
+            self.plots.export_to_xml()
+
+    def build_default_materials_and_geometry(self):
+        # Define materials.
+        fuel = openmc.Material(name='Fuel')
+        fuel.set_density('g/cm3', 10.29769)
+        fuel.add_nuclide("U234", 4.4843e-6)
+        fuel.add_nuclide("U235", 5.5815e-4)
+        fuel.add_nuclide("U238", 2.2408e-2)
+        fuel.add_nuclide("O16", 4.5829e-2)
+
+        clad = openmc.Material(name='Cladding')
+        clad.set_density('g/cm3', 6.55)
+        clad.add_nuclide("Zr90", 2.1827e-2)
+        clad.add_nuclide("Zr91", 4.7600e-3)
+        clad.add_nuclide("Zr92", 7.2758e-3)
+        clad.add_nuclide("Zr94", 7.3734e-3)
+        clad.add_nuclide("Zr96", 1.1879e-3)
+
+        hot_water = openmc.Material(name='Hot borated water')
+        hot_water.set_density('g/cm3', 0.740582)
+        hot_water.add_nuclide("H1", 4.9457e-2)
+        hot_water.add_nuclide("O16", 2.4672e-2)
+        hot_water.add_nuclide("B10", 8.0042e-6)
+        hot_water.add_nuclide("B11", 3.2218e-5)
+        hot_water.add_s_alpha_beta('c_H_in_H2O', '71t')
+
+        # Define the materials file.
+        self.materials.default_xs = '71c'
+        self.materials += (fuel, clad, hot_water)
+
+        # Instantiate ZCylinder surfaces
+        fuel_or = openmc.ZCylinder(x0=0, y0=0, R=0.39218, name='Fuel OR')
+        clad_or = openmc.ZCylinder(x0=0, y0=0, R=0.45720, name='Clad OR')
+
+        # Create boundary planes to surround the geometry
+        min_x = openmc.XPlane(x0=-10.71, boundary_type='reflective')
+        max_x = openmc.XPlane(x0=+10.71, boundary_type='reflective')
+        min_y = openmc.YPlane(y0=-10.71, boundary_type='reflective')
+        max_y = openmc.YPlane(y0=+10.71, boundary_type='reflective')
+
+        # Create a Universe to encapsulate a fuel pin
+        fuel_pin_universe = openmc.Universe(name='Fuel Pin')
+
+        # Create fuel Cell
+        fuel_cell = openmc.Cell(name='fuel')
+        fuel_cell.fill = fuel
+        fuel_cell.region = -fuel_or
+        fuel_pin_universe.add_cell(fuel_cell)
+
+        # Create a clad Cell
+        clad_cell = openmc.Cell(name='clad')
+        clad_cell.fill = clad
+        clad_cell.region = +fuel_or & -clad_or
+        fuel_pin_universe.add_cell(clad_cell)
+
+        # Create a moderator Cell
+        hot_water_cell = openmc.Cell(name='hot water')
+        hot_water_cell.fill = hot_water
+        hot_water_cell.region = +clad_or
+        fuel_pin_universe.add_cell(hot_water_cell)
+
+        # Create a Universe to encapsulate a control rod guide tube
+        guide_tube_universe = openmc.Universe(name='Guide Tube')
+
+        # Create guide tube inner Cell
+        gt_inner_cell = openmc.Cell(name='guide tube inner water')
+        gt_inner_cell.fill = hot_water
+        gt_inner_cell.region = -fuel_or
+        guide_tube_universe.add_cell(gt_inner_cell)
+
+        # Create a clad Cell
+        gt_clad_cell = openmc.Cell(name='guide tube clad')
+        gt_clad_cell.fill = clad
+        gt_clad_cell.region = +fuel_or & -clad_or
+        guide_tube_universe.add_cell(gt_clad_cell)
+
+        # Create a guide tube outer Cell
+        gt_outer_cell = openmc.Cell(name='guide tube outer water')
+        gt_outer_cell.fill = hot_water
+        gt_outer_cell.region = +clad_or
+        guide_tube_universe.add_cell(gt_outer_cell)
+
+        # Create fuel assembly Lattice
+        assembly = openmc.RectLattice(name='Fuel Assembly')
+        assembly.pitch = (1.26, 1.26)
+        assembly.lower_left = [-1.26 * 17. / 2.0] * 2
+
+        # Create array indices for guide tube locations in lattice
+        template_x = np.array([5, 8, 11, 3, 13, 2, 5, 8, 11, 14, 2, 5, 8,
+                               11, 14, 2, 5, 8, 11, 14, 3, 13, 5, 8, 11])
+        template_y = np.array([2, 2, 2, 3, 3, 5, 5, 5, 5, 5, 8, 8, 8, 8,
+                               8, 11, 11, 11, 11, 11, 13, 13, 14, 14, 14])
+
+        # Initialize an empty 17x17 array of the lattice universes
+        universes = np.empty((17, 17), dtype=openmc.Universe)
+
+        # Fill the array with the fuel pin and guide tube universes
+        universes[:,:] = fuel_pin_universe
+        universes[template_x, template_y] = guide_tube_universe
+
+        # Store the array of universes in the lattice
+        assembly.universes = universes
+
+        # Create root Cell
+        root_cell = openmc.Cell(name='root cell')
+        root_cell.fill = assembly
+
+        # Add boundary planes
+        root_cell.region = +min_x & -max_x & +min_y & -max_y
+
+        # Create root Universe
+        root_universe = openmc.Universe(universe_id=0, name='root universe')
+        root_universe.add_cell(root_cell)
+
+        # Instantiate a Geometry, register the root Universe, and export to XML
+        self.geometry.root_universe = root_universe
+
+    def build_default_settings(self):
+        self.settings.batches = 10
+        self.settings.inactive = 5
+        self.settings.particles = 100
+        self.settings.source = Source(space=Box([-10.71, -10.71, -1],
+                                                [10.71, 10.71, 1],
+                                                only_fissionable=True))
+
+    def build_defualt_plots(self):
+        plot = openmc.Plot()
+        plot.filename = 'mat'
+        plot.origin = (0.0, 0.0, 0)
+        plot.width = (21.42, 21.42)
+        plot.pixels = (300, 300)
+        plot.color = 'mat'
+
+        self.plots.add_plot(plot)
+
+
 class MGInputSet(InputSet):
     def build_default_materials_and_geometry(self):
         # Define materials needed for 1D/1G slab problem

tests/test_cmfd_feed/results_true.dat

@@ -124,92 +124,8 @@ tally 3:
 1.020705E+00
 5.413570E-02
 tally 4:
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
 3.049469E+00
 4.677325E-01
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-5.514939E+00
-1.528899E+00
 2.770358E+00
 3.879191E-01
 0.000000E+00
@@ -220,44 +136,8 @@ tally 4:
 0.000000E+00
 0.000000E+00
 0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-7.294002E+00
-2.675589E+00
+5.514939E+00
+1.528899E+00
 5.032131E+00
 1.275040E+00
 0.000000E+00
@@ -268,44 +148,8 @@ tally 4:
 0.000000E+00
 0.000000E+00
 0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-8.668860E+00
-3.776102E+00
+7.294002E+00
+2.675589E+00
 7.036008E+00
 2.490719E+00
 0.000000E+00
@@ -316,44 +160,8 @@ tally 4:
 0.000000E+00
 0.000000E+00
 0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-9.345868E+00
-4.380719E+00
+8.668860E+00
+3.776102E+00
 8.352414E+00
 3.501945E+00
 0.000000E+00
@@ -364,44 +172,8 @@ tally 4:
 0.000000E+00
 0.000000E+00
 0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
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@@ -556,44 +220,8 @@ tally 4:
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@@ -604,44 +232,8 @@ tally 4:
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@@ -652,6 +244,414 @@ tally 4:
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 cmfd indices
 1.000000E+01
 1.000000E+00

tests/test_cmfd_nofeed/results_true.dat

@@ -124,92 +124,8 @@ tally 3:
 9.213728E-01
 4.422001E-02
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 1.000000E+01
 1.000000E+00

tests/test_filter_mesh_2d/results_true.dat

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@@ -525,24 +525,16 @@ tally 1:
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@@ -565,6 +557,14 @@ tally 1:
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tests/test_mgxs_library_condense/inputs_true.dat

@@ -1 +1 @@
-e2cdca7ea5b3532050af5b12fac26d7ef212d2696bb1b73cdd00929b2243c40d100ad02438c7b090555b49815d0de6c48cf1b4ebf437a48bc80c2d2b4bad292e
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tests/test_mgxs_library_condense/results_true.dat

@@ -40,6 +40,27 @@
 0     10000         1   total  4.996730e-07  3.650635e-08
    material  group in nuclide      mean  std. dev.
 0     10000         1   total  0.090004   0.006367
+   material  delayedgroup  group in nuclide      mean  std. dev.
+0     10000             1         1   total  0.000021   0.000001
+1     10000             2         1   total  0.000110   0.000008
+2     10000             3         1   total  0.000107   0.000007
+3     10000             4         1   total  0.000249   0.000017
+4     10000             5         1   total  0.000112   0.000007
+5     10000             6         1   total  0.000046   0.000003
+   material  delayedgroup  group out nuclide  mean  std. dev.
+0     10000             1          1   total   0.0   0.000000
+1     10000             2          1   total   1.0   0.869128
+2     10000             3          1   total   1.0   1.414214
+3     10000             4          1   total   1.0   0.360359
+4     10000             5          1   total   0.0   0.000000
+5     10000             6          1   total   0.0   0.000000
+   material  delayedgroup  group in nuclide      mean  std. dev.
+0     10000             1         1   total  0.000227   0.000020
+1     10000             2         1   total  0.001214   0.000108
+2     10000             3         1   total  0.001184   0.000104
+3     10000             4         1   total  0.002752   0.000240
+4     10000             5         1   total  0.001231   0.000105
+5     10000             6         1   total  0.000512   0.000044
    material  group in nuclide      mean  std. dev.
 0     10001         1   total  0.311594   0.013793
    material  group in nuclide      mean  std. dev.
@@ -82,6 +103,27 @@
 0     10001         1   total  5.454760e-07  4.949800e-08
    material  group in nuclide  mean  std. dev.
 0     10001         1   total   0.0        0.0
+   material  delayedgroup  group in nuclide  mean  std. dev.
+0     10001             1         1   total   0.0        0.0
+1     10001             2         1   total   0.0        0.0
+2     10001             3         1   total   0.0        0.0
+3     10001             4         1   total   0.0        0.0
+4     10001             5         1   total   0.0        0.0
+5     10001             6         1   total   0.0        0.0
+   material  delayedgroup  group out nuclide  mean  std. dev.
+0     10001             1          1   total   0.0        0.0
+1     10001             2          1   total   0.0        0.0
+2     10001             3          1   total   0.0        0.0
+3     10001             4          1   total   0.0        0.0
+4     10001             5          1   total   0.0        0.0
+5     10001             6          1   total   0.0        0.0
+   material  delayedgroup  group in nuclide  mean  std. dev.
+0     10001             1         1   total   0.0        0.0
+1     10001             2         1   total   0.0        0.0
+2     10001             3         1   total   0.0        0.0
+3     10001             4         1   total   0.0        0.0
+4     10001             5         1   total   0.0        0.0
+5     10001             6         1   total   0.0        0.0
    material  group in nuclide      mean  std. dev.
 0     10002         1   total  0.904999   0.043964
    material  group in nuclide      mean  std. dev.
@@ -124,3 +166,24 @@
 0     10002         1   total  5.773006e-07  5.322132e-08
    material  group in nuclide  mean  std. dev.
 0     10002         1   total   0.0        0.0
+   material  delayedgroup  group in nuclide  mean  std. dev.
+0     10002             1         1   total   0.0        0.0
+1     10002             2         1   total   0.0        0.0
+2     10002             3         1   total   0.0        0.0
+3     10002             4         1   total   0.0        0.0
+4     10002             5         1   total   0.0        0.0
+5     10002             6         1   total   0.0        0.0
+   material  delayedgroup  group out nuclide  mean  std. dev.
+0     10002             1          1   total   0.0        0.0
+1     10002             2          1   total   0.0        0.0
+2     10002             3          1   total   0.0        0.0
+3     10002             4          1   total   0.0        0.0
+4     10002             5          1   total   0.0        0.0
+5     10002             6          1   total   0.0        0.0
+   material  delayedgroup  group in nuclide  mean  std. dev.
+0     10002             1         1   total   0.0        0.0
+1     10002             2         1   total   0.0        0.0
+2     10002             3         1   total   0.0        0.0
+3     10002             4         1   total   0.0        0.0
+4     10002             5         1   total   0.0        0.0
+5     10002             6         1   total   0.0        0.0

tests/test_mgxs_library_condense/test_mgxs_library_condense.py

@@ -23,12 +23,18 @@ class MGXSTestHarness(PyAPITestHarness):
         energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 0.625e-6,
                                                               20.])
 
+        # Initialize a six-delayed-group structure
+        delayed_groups = list(range(1,7))
+
         # Initialize MGXS Library for a few cross section types
         self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry)
         self.mgxs_lib.by_nuclide = False
+
         # Test all MGXS types
-        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES
+        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES + \
+                                   openmc.mgxs.MDGXS_TYPES
         self.mgxs_lib.energy_groups = energy_groups
+        self.mgxs_lib.delayed_groups = delayed_groups
         self.mgxs_lib.legendre_order = 3
         self.mgxs_lib.domain_type = 'material'
         self.mgxs_lib.build_library()

tests/test_mgxs_library_distribcell/inputs_true.dat

@@ -1 +1 @@
-2d948f3b12293294eaeca231a3df9d51195379e8bb38dd3e68d3bc512a7d08ed52a1109054ca381684ec127268710f6d6e9210ac8154c9b379608e996627624a
+9ce3d6987d67e92b0924916bb54288429d2bd6dfd12a69f86c5dbefb407f7eb72adb0e44d558c09e9a39610ffeb651aee4aedc629cf3a28a181d62ca4cfbcd5a

tests/test_mgxs_library_distribcell/results_true.dat

@@ -1,42 +1,63 @@
                                     avg(distribcell)  group in nuclide      mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  1.145934   0.553822
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.457353   0.010474
                                     avg(distribcell)  group in nuclide      mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.718919   0.520644
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.405649   0.015784
                                     avg(distribcell)  group in nuclide      mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.718919   0.520644
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.405641   0.015787
                                     avg(distribcell)  group in nuclide      mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.019762   0.010629
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.066556    0.00251
                                     avg(distribcell)  group in nuclide      mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.019762   0.010629
-                                    avg(distribcell)  group in nuclide  mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total   0.0        0.0
-                                    avg(distribcell)  group in nuclide  mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total   0.0        0.0
-                                    avg(distribcell)  group in nuclide  mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total   0.0        0.0
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.028979   0.002712
                                     avg(distribcell)  group in nuclide      mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  1.126172    0.54344
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.037577   0.001487
                                     avg(distribcell)  group in nuclide      mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  1.142547   0.570131
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.092377   0.003628
+                                    avg(distribcell)  group in nuclide      mean  std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  7.276707   0.287579
+                                    avg(distribcell)  group in nuclide      mean  std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.390797   0.008717
+                                    avg(distribcell)  group in nuclide      mean  std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.387332   0.014241
                                     avg(distribcell)  group in  group out nuclide moment      mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P0  1.142547   0.570131
-1  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P1  0.447381   0.216322
-2  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P2  0.141202   0.066504
-3  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P3  0.039228   0.024621
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P0  0.387009   0.014230
+1  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P1  0.047179   0.004923
+2  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P2  0.015713   0.003654
+3  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P3  0.005378   0.003137
                                     avg(distribcell)  group in  group out nuclide moment      mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P0  1.142547   0.570131
-1  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P1  0.447381   0.216322
-2  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P2  0.141202   0.066504
-3  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P3  0.039228   0.024621
-                                    avg(distribcell)  group in  group out nuclide  mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total   1.0   0.529717
-                                    avg(distribcell)  group in  group out nuclide  mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total   0.0        0.0
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P0  0.387332   0.014241
+1  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P1  0.047187   0.004933
+2  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P2  0.015727   0.003654
+3  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P3  0.005387   0.003141
+                                    avg(distribcell)  group in  group out nuclide      mean  std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total  1.000834   0.037242
+                                    avg(distribcell)  group in  group out nuclide      mean  std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total  0.094516     0.0059
                                     avg(distribcell)  group out nuclide  mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...          1   total   0.0        0.0
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...          1   total   1.0   0.080455
                                     avg(distribcell)  group out nuclide  mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...          1   total   0.0        0.0
-                                    avg(distribcell)  group in nuclide      mean     std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.000001  6.946255e-07
-                                    avg(distribcell)  group in nuclide  mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total   0.0        0.0
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...          1   total   1.0   0.080541
+                                    avg(distribcell)  group in nuclide          mean     std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  5.139437e-07  2.133314e-08
+                                    avg(distribcell)  group in nuclide      mean  std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.091725   0.003604
+                                    avg(distribcell)  delayedgroup  group in nuclide      mean     std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             1         1   total  0.000021  8.253907e-07
+1  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             2         1   total  0.000112  4.284000e-06
+2  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             3         1   total  0.000109  4.105197e-06
+3  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             4         1   total  0.000252  9.271420e-06
+4  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             5         1   total  0.000112  3.888625e-06
+5  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             6         1   total  0.000047  1.625563e-06
+                                    avg(distribcell)  delayedgroup  group out nuclide  mean  std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             1          1   total   0.0   0.000000
+1  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             2          1   total   1.0   1.414214
+2  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             3          1   total   1.0   1.414214
+3  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             4          1   total   0.0   0.000000
+4  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             5          1   total   0.0   0.000000
+5  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             6          1   total   1.0   1.414214
+                                    avg(distribcell)  delayedgroup  group in nuclide      mean  std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             1         1   total  0.000227   0.000012
+1  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             2         1   total  0.001209   0.000061
+2  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             3         1   total  0.001177   0.000059
+3  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             4         1   total  0.002727   0.000135
+4  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             5         1   total  0.001210   0.000058
+5  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             6         1   total  0.000504   0.000024

tests/test_mgxs_library_distribcell/test_mgxs_library_distribcell.py

@@ -6,29 +6,39 @@ import glob
 import hashlib
 sys.path.insert(0, os.pardir)
 from testing_harness import PyAPITestHarness
+from input_set import AssemblyInputSet
 import openmc
 import openmc.mgxs
 
 
 class MGXSTestHarness(PyAPITestHarness):
     def _build_inputs(self):
+        # Set the input set to use the pincell model
+        self._input_set = AssemblyInputSet()
+
         # Generate inputs using parent class routine
         super(MGXSTestHarness, self)._build_inputs()
 
         # Initialize a one-group structure
         energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 20.])
 
+        # Initialize a six-delayed-group structure
+        delayed_groups = list(range(1,7))
+
         # Initialize MGXS Library for a few cross section types
         # for one material-filled cell in the geometry
         self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry)
         self.mgxs_lib.by_nuclide = False
+
         # Test all MGXS types
-        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES
+        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES + \
+                                   openmc.mgxs.MDGXS_TYPES
         self.mgxs_lib.energy_groups = energy_groups
+        self.mgxs_lib.delayed_groups = delayed_groups
         self.mgxs_lib.legendre_order = 3
         self.mgxs_lib.domain_type = 'distribcell'
-        material_cells = self.mgxs_lib.openmc_geometry.get_all_material_cells()
-        self.mgxs_lib.domains = [material_cells[-1]]
+        cells = self.mgxs_lib.openmc_geometry.get_all_material_cells()
+        self.mgxs_lib.domains = [c for c in cells if c.name == 'fuel']
         self.mgxs_lib.build_library()
 
         # Initialize a tallies file

tests/test_mgxs_library_hdf5/inputs_true.dat

@@ -1 +1 @@
-e2cdca7ea5b3532050af5b12fac26d7ef212d2696bb1b73cdd00929b2243c40d100ad02438c7b090555b49815d0de6c48cf1b4ebf437a48bc80c2d2b4bad292e
+08c5f1c783dd88c5fed51c054718ca09fc4e99aa4560a6f928b3902991948f3a878d055ac46c07548904285c2c5f22dc2a3d8c1bb82b8e73d76dd790820117df

tests/test_mgxs_library_hdf5/results_true.dat

@@ -72,6 +72,45 @@ domain=10000 type=inverse-velocity
 domain=10000 type=prompt-nu-fission
 [ 0.01923922  0.46671903]
 [ 0.00130951  0.04141087]
+domain=10000 type=delayed-nu-fission
+[[  2.29808234e-05   1.06974158e-04]
+ [  1.43606337e-04   5.52167907e-04]
+ [  1.51382216e-04   5.27147681e-04]
+ [  7.42603178e-05   2.22018043e-04]
+ [  4.14908454e-05   9.10244403e-05]
+ [  1.70016000e-05   3.81298119e-05]]
+[[  1.66363133e-06   9.49156242e-06]
+ [  1.05907806e-05   4.89925426e-05]
+ [  1.12671238e-05   4.67725567e-05]
+ [  5.22610273e-06   1.87563195e-05]
+ [  2.99830766e-06   7.68984041e-06]
+ [  1.22654684e-06   3.22124663e-06]]
+domain=10000 type=chi-delayed
+[[ 0.  0.]
+ [ 1.  0.]
+ [ 1.  0.]
+ [ 1.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+[[ 0.          0.        ]
+ [ 0.86912776  0.        ]
+ [ 1.41421356  0.        ]
+ [ 0.36035904  0.        ]
+ [ 0.          0.        ]
+ [ 0.          0.        ]]
+domain=10000 type=beta
+[[  4.89188107e-05   2.27713711e-04]
+ [  3.05691886e-04   1.17538858e-03]
+ [  3.22244241e-04   1.12212853e-03]
+ [  3.82159891e-03   1.14255357e-02]
+ [  2.13520995e-03   4.68431744e-03]
+ [  8.74939644e-04   1.96224379e-03]]
+[[  4.67388620e-06   2.46946810e-05]
+ [  2.95223877e-05   1.27466393e-04]
+ [  3.12885004e-05   1.21690543e-04]
+ [  3.21434855e-04   1.09939816e-03]
+ [  1.82980497e-04   4.50738567e-04]
+ [  7.48899920e-05   1.88812772e-04]]
 domain=10001 type=total
 [ 0.31373767  0.3008214 ]
 [ 0.0155819   0.02805245]
@@ -146,6 +185,45 @@ domain=10001 type=inverse-velocity
 domain=10001 type=prompt-nu-fission
 [ 0.  0.]
 [ 0.  0.]
+domain=10001 type=delayed-nu-fission
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+domain=10001 type=chi-delayed
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+domain=10001 type=beta
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
 domain=10002 type=total
 [ 0.66457226  2.05238401]
 [ 0.03121475  0.22434291]
@@ -220,3 +298,42 @@ domain=10002 type=inverse-velocity
 domain=10002 type=prompt-nu-fission
 [ 0.  0.]
 [ 0.  0.]
+domain=10002 type=delayed-nu-fission
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+domain=10002 type=chi-delayed
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+domain=10002 type=beta
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]

tests/test_mgxs_library_hdf5/test_mgxs_library_hdf5.py

@@ -24,12 +24,18 @@ class MGXSTestHarness(PyAPITestHarness):
         energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 0.625e-6,
                                                               20.])
 
+        # Initialize a six-delayed-group structure
+        delayed_groups = list(range(1,7))
+
         # Initialize MGXS Library for a few cross section types
         self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry)
         self.mgxs_lib.by_nuclide = False
+
         # Test all MGXS types
-        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES
+        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES + \
+                                   openmc.mgxs.MDGXS_TYPES
         self.mgxs_lib.energy_groups = energy_groups
+        self.mgxs_lib.delayed_groups = delayed_groups
         self.mgxs_lib.legendre_order = 3
         self.mgxs_lib.domain_type = 'material'
         self.mgxs_lib.build_library()

tests/test_mgxs_library_mesh/inputs_true.dat

@@ -1 +1 @@
-a4cd030bea212e45fdb159e75a7fb3d1947e9bf3d0384ac5d37a72298d67dcfdd1b9eb5c6af8ac6e5983bd5b47de9c17a2ea472b467b7222a4909ee070bf1ca3
+5f167bdd4d6ae5873d48483e85aceaec8a934239ed5a50ef6f6500ce204f5851ae330621a5007f3b3d6bdab49f2cd627d011c1f6e6983fec958a6984eb9cb7ca

tests/test_mgxs_library_mesh/results_true.dat

@@ -1,62 +1,62 @@
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  0.640786  0.044177
-1      1  2  1        1   total  0.660597  0.128423
-2      2  1  1        1   total  0.615276  0.104046
+1      1  2  1        1   total  0.615276  0.104046
+2      2  1  1        1   total  0.660597  0.128423
 3      2  2  1        1   total  0.646999  0.186709
   mesh 1       group in nuclide     mean std. dev.
        x  y  z                                    
 0      1  1  1        1   total  0.36665  0.048814
-1      1  2  1        1   total  0.40784  0.096486
-2      2  1  1        1   total  0.36356  0.074111
+1      1  2  1        1   total  0.36356  0.074111
+2      2  1  1        1   total  0.40784  0.096486
 3      2  2  1        1   total  0.41456  0.160443
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  0.366650  0.048814
-1      1  2  1        1   total  0.407840  0.096486
-2      2  1  1        1   total  0.363560  0.074111
+1      1  2  1        1   total  0.363560  0.074111
+2      2  1  1        1   total  0.407840  0.096486
 3      2  2  1        1   total  0.414593  0.160436
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  0.025749  0.002863
-1      1  2  1        1   total  0.028400  0.005275
-2      2  1  1        1   total  0.022988  0.004099
+1      1  2  1        1   total  0.022988  0.004099
+2      2  1  1        1   total  0.028400  0.005275
 3      2  2  1        1   total  0.027589  0.010350
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  0.015861  0.002876
-1      1  2  1        1   total  0.017280  0.004371
-2      2  1  1        1   total  0.014403  0.003542
+1      1  2  1        1   total  0.014403  0.003542
+2      2  1  1        1   total  0.017280  0.004371
 3      2  2  1        1   total  0.018061  0.010110
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  0.009888  0.001077
-1      1  2  1        1   total  0.011121  0.002456
-2      2  1  1        1   total  0.008585  0.001552
+1      1  2  1        1   total  0.008585  0.001552
+2      2  1  1        1   total  0.011121  0.002456
 3      2  2  1        1   total  0.009527  0.003659
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  0.026065  0.002907
-1      1  2  1        1   total  0.029084  0.006430
-2      2  1  1        1   total  0.022596  0.004062
+1      1  2  1        1   total  0.022596  0.004062
+2      2  1  1        1   total  0.029084  0.006430
 3      2  2  1        1   total  0.025066  0.009687
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  1.938476  0.211550
-1      1  2  1        1   total  2.177360  0.480780
-2      2  1  1        1   total  1.682799  0.303764
+1      1  2  1        1   total  1.682799  0.303764
+2      2  1  1        1   total  2.177360  0.480780
 3      2  2  1        1   total  1.864890  0.715661
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  0.615037  0.041754
-1      1  2  1        1   total  0.632196  0.123878
-2      2  1  1        1   total  0.592288  0.100439
+1      1  2  1        1   total  0.592288  0.100439
+2      2  1  1        1   total  0.632196  0.123878
 3      2  2  1        1   total  0.619410  0.177190
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  0.584014  0.054315
-1      1  2  1        1   total  0.622514  0.111323
-2      2  1  1        1   total  0.587256  0.084833
+1      1  2  1        1   total  0.587256  0.084833
+2      2  1  1        1   total  0.622514  0.111323
 3      2  2  1        1   total  0.613792  0.168612
    mesh 1       group in group out nuclide moment      mean std. dev.
         x  y  z                                                      
@@ -64,14 +64,14 @@
 1       1  1  1        1         1   total     P1  0.243427  0.025488
 2       1  1  1        1         1   total     P2  0.089236  0.007357
 3       1  1  1        1         1   total     P3  0.008994  0.005768
-4       1  2  1        1         1   total     P0  0.622514  0.111323
-5       1  2  1        1         1   total     P1  0.239376  0.042594
-6       1  2  1        1         1   total     P2  0.088386  0.017200
-7       1  2  1        1         1   total     P3 -0.001243  0.005639
-8       2  1  1        1         1   total     P0  0.587256  0.084833
-9       2  1  1        1         1   total     P1  0.245120  0.041033
-10      2  1  1        1         1   total     P2  0.086784  0.016255
-11      2  1  1        1         1   total     P3  0.008660  0.004755
+4       1  2  1        1         1   total     P0  0.587256  0.084833
+5       1  2  1        1         1   total     P1  0.245120  0.041033
+6       1  2  1        1         1   total     P2  0.086784  0.016255
+7       1  2  1        1         1   total     P3  0.008660  0.004755
+8       2  1  1        1         1   total     P0  0.622514  0.111323
+9       2  1  1        1         1   total     P1  0.239376  0.042594
+10      2  1  1        1         1   total     P2  0.088386  0.017200
+11      2  1  1        1         1   total     P3 -0.001243  0.005639
 12      2  2  1        1         1   total     P0  0.612950  0.167940
 13      2  2  1        1         1   total     P1  0.226176  0.061882
 14      2  2  1        1         1   total     P2  0.086593  0.026126
@@ -82,14 +82,14 @@
 1       1  1  1        1         1   total     P1  0.243427  0.025488
 2       1  1  1        1         1   total     P2  0.089236  0.007357
 3       1  1  1        1         1   total     P3  0.008994  0.005768
-4       1  2  1        1         1   total     P0  0.622514  0.111323
-5       1  2  1        1         1   total     P1  0.239376  0.042594
-6       1  2  1        1         1   total     P2  0.088386  0.017200
-7       1  2  1        1         1   total     P3 -0.001243  0.005639
-8       2  1  1        1         1   total     P0  0.587256  0.084833
-9       2  1  1        1         1   total     P1  0.245120  0.041033
-10      2  1  1        1         1   total     P2  0.086784  0.016255
-11      2  1  1        1         1   total     P3  0.008660  0.004755
+4       1  2  1        1         1   total     P0  0.587256  0.084833
+5       1  2  1        1         1   total     P1  0.245120  0.041033
+6       1  2  1        1         1   total     P2  0.086784  0.016255
+7       1  2  1        1         1   total     P3  0.008660  0.004755
+8       2  1  1        1         1   total     P0  0.622514  0.111323
+9       2  1  1        1         1   total     P1  0.239376  0.042594
+10      2  1  1        1         1   total     P2  0.088386  0.017200
+11      2  1  1        1         1   total     P3 -0.001243  0.005639
 12      2  2  1        1         1   total     P0  0.613792  0.168612
 13      2  2  1        1         1   total     P1  0.226142  0.061856
 14      2  2  1        1         1   total     P2  0.086174  0.025979
@@ -97,36 +97,114 @@
   mesh 1       group in group out nuclide      mean std. dev.
        x  y  z                                               
 0      1  1  1        1         1   total  1.000000  0.088094
-1      1  2  1        1         1   total  1.000000  0.160891
-2      2  1  1        1         1   total  1.000000  0.126864
+1      1  2  1        1         1   total  1.000000  0.126864
+2      2  1  1        1         1   total  1.000000  0.160891
 3      2  2  1        1         1   total  1.001374  0.305883
   mesh 1       group in group out nuclide      mean std. dev.
        x  y  z                                               
 0      1  1  1        1         1   total  0.027395  0.004680
-1      1  2  1        1         1   total  0.022914  0.006025
-2      2  1  1        1         1   total  0.019384  0.002846
+1      1  2  1        1         1   total  0.019384  0.002846
+2      2  1  1        1         1   total  0.022914  0.006025
 3      2  2  1        1         1   total  0.029629  0.006292
   mesh 1       group out nuclide mean std. dev.
        x  y  z                                 
 0      1  1  1         1   total  1.0  0.220956
-1      1  2  1         1   total  1.0  0.316565
-2      2  1  1         1   total  1.0  0.132140
+1      1  2  1         1   total  1.0  0.132140
+2      2  1  1         1   total  1.0  0.316565
 3      2  2  1         1   total  1.0  0.181577
   mesh 1       group out nuclide mean std. dev.
        x  y  z                                 
 0      1  1  1         1   total  1.0  0.222246
-1      1  2  1         1   total  1.0  0.316565
-2      2  1  1         1   total  1.0  0.132140
+1      1  2  1         1   total  1.0  0.132140
+2      2  1  1         1   total  1.0  0.316565
 3      2  2  1         1   total  1.0  0.181577
   mesh 1       group in nuclide          mean     std. dev.
        x  y  z                                             
 0      1  1  1        1   total  3.610522e-07  3.169931e-08
-1      1  2  1        1   total  3.942353e-07  8.459167e-08
-2      2  1  1        1   total  3.097784e-07  5.252025e-08
+1      1  2  1        1   total  3.097784e-07  5.252025e-08
+2      2  1  1        1   total  3.942353e-07  8.459167e-08
 3      2  2  1        1   total  3.799163e-07  1.806470e-07
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  0.025920  0.002893
-1      1  2  1        1   total  0.028922  0.006394
-2      2  1  1        1   total  0.022467  0.004039
+1      1  2  1        1   total  0.022467  0.004039
+2      2  1  1        1   total  0.028922  0.006394
 3      2  2  1        1   total  0.024923  0.009632
+   mesh 1       delayedgroup group in nuclide      mean     std. dev.
+        x  y  z                                                      
+0       1  1  1            1        1   total  0.000004  4.432732e-07
+1       1  1  1            2        1   total  0.000026  2.653319e-06
+2       1  1  1            3        1   total  0.000024  2.402270e-06
+3       1  1  1            4        1   total  0.000054  5.464055e-06
+4       1  1  1            5        1   total  0.000026  2.663025e-06
+5       1  1  1            6        1   total  0.000010  1.038005e-06
+6       1  2  1            1        1   total  0.000004  6.987770e-07
+7       1  2  1            2        1   total  0.000023  4.115234e-06
+8       1  2  1            3        1   total  0.000021  3.816392e-06
+9       1  2  1            4        1   total  0.000049  8.885822e-06
+10      1  2  1            5        1   total  0.000024  4.378290e-06
+11      1  2  1            6        1   total  0.000009  1.745695e-06
+12      2  1  1            1        1   total  0.000005  1.098837e-06
+13      2  1  1            2        1   total  0.000029  6.436855e-06
+14      2  1  1            3        1   total  0.000027  5.926286e-06
+15      2  1  1            4        1   total  0.000061  1.359391e-05
+16      2  1  1            5        1   total  0.000029  6.489015e-06
+17      2  1  1            6        1   total  0.000011  2.574270e-06
+18      2  2  1            1        1   total  0.000004  1.660497e-06
+19      2  2  1            2        1   total  0.000025  9.701974e-06
+20      2  2  1            3        1   total  0.000023  9.005217e-06
+21      2  2  1            4        1   total  0.000054  2.084107e-05
+22      2  2  1            5        1   total  0.000026  9.981045e-06
+23      2  2  1            6        1   total  0.000010  3.987979e-06
+   mesh 1       delayedgroup group out nuclide mean std. dev.
+        x  y  z                                              
+0       1  1  1            1         1   total  0.0  0.000000
+1       1  1  1            2         1   total  0.0  0.000000
+2       1  1  1            3         1   total  0.0  0.000000
+3       1  1  1            4         1   total  1.0  1.414214
+4       1  1  1            5         1   total  0.0  0.000000
+5       1  1  1            6         1   total  0.0  0.000000
+6       1  2  1            1         1   total  0.0  0.000000
+7       1  2  1            2         1   total  0.0  0.000000
+8       1  2  1            3         1   total  0.0  0.000000
+9       1  2  1            4         1   total  0.0  0.000000
+10      1  2  1            5         1   total  0.0  0.000000
+11      1  2  1            6         1   total  0.0  0.000000
+12      2  1  1            1         1   total  0.0  0.000000
+13      2  1  1            2         1   total  0.0  0.000000
+14      2  1  1            3         1   total  0.0  0.000000
+15      2  1  1            4         1   total  0.0  0.000000
+16      2  1  1            5         1   total  0.0  0.000000
+17      2  1  1            6         1   total  0.0  0.000000
+18      2  2  1            1         1   total  0.0  0.000000
+19      2  2  1            2         1   total  0.0  0.000000
+20      2  2  1            3         1   total  0.0  0.000000
+21      2  2  1            4         1   total  0.0  0.000000
+22      2  2  1            5         1   total  0.0  0.000000
+23      2  2  1            6         1   total  0.0  0.000000
+   mesh 1       delayedgroup group in nuclide      mean std. dev.
+        x  y  z                                                  
+0       1  1  1            1        1   total  0.000166  0.000023
+1       1  1  1            2        1   total  0.000989  0.000136
+2       1  1  1            3        1   total  0.000907  0.000123
+3       1  1  1            4        1   total  0.002087  0.000282
+4       1  1  1            5        1   total  0.001014  0.000137
+5       1  1  1            6        1   total  0.000400  0.000054
+6       1  2  1            1        1   total  0.000167  0.000030
+7       1  2  1            2        1   total  0.001002  0.000178
+8       1  2  1            3        1   total  0.000926  0.000165
+9       1  2  1            4        1   total  0.002149  0.000384
+10      1  2  1            5        1   total  0.001056  0.000189
+11      1  2  1            6        1   total  0.000417  0.000076
+12      2  1  1            1        1   total  0.000171  0.000039
+13      2  1  1            2        1   total  0.001003  0.000226
+14      2  1  1            3        1   total  0.000918  0.000208
+15      2  1  1            4        1   total  0.002100  0.000477
+16      2  1  1            5        1   total  0.000996  0.000228
+17      2  1  1            6        1   total  0.000394  0.000090
+18      2  2  1            1        1   total  0.000171  0.000082
+19      2  2  1            2        1   total  0.001007  0.000480
+20      2  2  1            3        1   total  0.000929  0.000445
+21      2  2  1            4        1   total  0.002143  0.001028
+22      2  2  1            5        1   total  0.001026  0.000492
+23      2  2  1            6        1   total  0.000408  0.000196

tests/test_mgxs_library_mesh/test_mgxs_library_mesh.py

@@ -18,14 +18,19 @@ class MGXSTestHarness(PyAPITestHarness):
         # Initialize a one-group structure
         energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 20.])
 
+        # Initialize a six-delayed-group structure
+        delayed_groups = list(range(1,7))
+
         # Initialize MGXS Library for a few cross section types
         # for one material-filled cell in the geometry
         self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry)
         self.mgxs_lib.by_nuclide = False
 
         # Test all MGXS types
-        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES
+        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES + \
+                                   openmc.mgxs.MDGXS_TYPES
         self.mgxs_lib.energy_groups = energy_groups
+        self.mgxs_lib.delayed_groups = delayed_groups
         self.mgxs_lib.legendre_order = 3
         self.mgxs_lib.domain_type = 'mesh'
 

tests/test_mgxs_library_no_nuclides/inputs_true.dat

@@ -1 +1 @@
-e2cdca7ea5b3532050af5b12fac26d7ef212d2696bb1b73cdd00929b2243c40d100ad02438c7b090555b49815d0de6c48cf1b4ebf437a48bc80c2d2b4bad292e
+08c5f1c783dd88c5fed51c054718ca09fc4e99aa4560a6f928b3902991948f3a878d055ac46c07548904285c2c5f22dc2a3d8c1bb82b8e73d76dd790820117df

tests/test_mgxs_library_no_nuclides/results_true.dat

@@ -29,39 +29,39 @@
 1     10000         1   total  0.385188   0.026946
 0     10000         2   total  0.412389   0.015425
     material  group in  group out nuclide moment      mean  std. dev.
-12     10000         1          1   total     P0  0.384199   0.027001
-13     10000         1          1   total     P1  0.051870   0.006983
-14     10000         1          1   total     P2  0.020069   0.002846
+9      10000         1          1   total     P0 -0.000207   0.000149
+11     10000         1          1   total     P1  0.000234   0.000128
+13     10000         1          1   total     P2  0.051870   0.006983
 15     10000         1          1   total     P3  0.009478   0.002234
 8      10000         1          2   total     P0  0.000989   0.000482
-9      10000         1          2   total     P1 -0.000207   0.000149
-10     10000         1          2   total     P2 -0.000103   0.000184
-11     10000         1          2   total     P3  0.000234   0.000128
-4      10000         2          1   total     P0  0.000925   0.000925
-5      10000         2          1   total     P1 -0.000768   0.000768
-6      10000         2          1   total     P2  0.000494   0.000494
+10     10000         1          2   total     P1 -0.000103   0.000184
+12     10000         1          2   total     P2  0.384199   0.027001
+14     10000         1          2   total     P3  0.020069   0.002846
+1      10000         2          1   total     P0  0.016482   0.004502
+3      10000         2          1   total     P1 -0.010499   0.010438
+5      10000         2          1   total     P2 -0.000768   0.000768
 7      10000         2          1   total     P3 -0.000171   0.000172
 0      10000         2          2   total     P0  0.411465   0.015245
-1      10000         2          2   total     P1  0.016482   0.004502
-2      10000         2          2   total     P2  0.006371   0.010551
-3      10000         2          2   total     P3 -0.010499   0.010438
+2      10000         2          2   total     P1  0.006371   0.010551
+4      10000         2          2   total     P2  0.000925   0.000925
+6      10000         2          2   total     P3  0.000494   0.000494
     material  group in  group out nuclide moment      mean  std. dev.
-12     10000         1          1   total     P0  0.384199   0.027001
-13     10000         1          1   total     P1  0.051870   0.006983
-14     10000         1          1   total     P2  0.020069   0.002846
+9      10000         1          1   total     P0 -0.000207   0.000149
+11     10000         1          1   total     P1  0.000234   0.000128
+13     10000         1          1   total     P2  0.051870   0.006983
 15     10000         1          1   total     P3  0.009478   0.002234
 8      10000         1          2   total     P0  0.000989   0.000482
-9      10000         1          2   total     P1 -0.000207   0.000149
-10     10000         1          2   total     P2 -0.000103   0.000184
-11     10000         1          2   total     P3  0.000234   0.000128
-4      10000         2          1   total     P0  0.000925   0.000925
-5      10000         2          1   total     P1 -0.000768   0.000768
-6      10000         2          1   total     P2  0.000494   0.000494
+10     10000         1          2   total     P1 -0.000103   0.000184
+12     10000         1          2   total     P2  0.384199   0.027001
+14     10000         1          2   total     P3  0.020069   0.002846
+1      10000         2          1   total     P0  0.016482   0.004502
+3      10000         2          1   total     P1 -0.010499   0.010438
+5      10000         2          1   total     P2 -0.000768   0.000768
 7      10000         2          1   total     P3 -0.000171   0.000172
 0      10000         2          2   total     P0  0.411465   0.015245
-1      10000         2          2   total     P1  0.016482   0.004502
-2      10000         2          2   total     P2  0.006371   0.010551
-3      10000         2          2   total     P3 -0.010499   0.010438
+2      10000         2          2   total     P1  0.006371   0.010551
+4      10000         2          2   total     P2  0.000925   0.000925
+6      10000         2          2   total     P3  0.000494   0.000494
    material  group in  group out nuclide  mean  std. dev.
 3     10000         1          1   total   1.0   0.078516
 2     10000         1          2   total   1.0   0.687184
@@ -84,6 +84,45 @@
    material  group in nuclide      mean  std. dev.
 1     10000         1   total  0.019239   0.001310
 0     10000         2   total  0.466719   0.041411
+    material  delayedgroup  group in nuclide      mean  std. dev.
+1      10000             1         1   total  0.000023   0.000002
+3      10000             2         1   total  0.000144   0.000011
+5      10000             3         1   total  0.000151   0.000011
+7      10000             4         1   total  0.000074   0.000005
+9      10000             5         1   total  0.000041   0.000003
+11     10000             6         1   total  0.000017   0.000001
+0      10000             1         2   total  0.000107   0.000009
+2      10000             2         2   total  0.000552   0.000049
+4      10000             3         2   total  0.000527   0.000047
+6      10000             4         2   total  0.000222   0.000019
+8      10000             5         2   total  0.000091   0.000008
+10     10000             6         2   total  0.000038   0.000003
+    material  delayedgroup  group out nuclide  mean  std. dev.
+1      10000             1          1   total   0.0   0.000000
+3      10000             2          1   total   1.0   0.869128
+5      10000             3          1   total   1.0   1.414214
+7      10000             4          1   total   1.0   0.360359
+9      10000             5          1   total   0.0   0.000000
+11     10000             6          1   total   0.0   0.000000
+0      10000             1          2   total   0.0   0.000000
+2      10000             2          2   total   0.0   0.000000
+4      10000             3          2   total   0.0   0.000000
+6      10000             4          2   total   0.0   0.000000
+8      10000             5          2   total   0.0   0.000000
+10     10000             6          2   total   0.0   0.000000
+    material  delayedgroup  group in nuclide      mean  std. dev.
+1      10000             1         1   total  0.000049   0.000005
+3      10000             2         1   total  0.000306   0.000030
+5      10000             3         1   total  0.000322   0.000031
+7      10000             4         1   total  0.003822   0.000321
+9      10000             5         1   total  0.002135   0.000183
+11     10000             6         1   total  0.000875   0.000075
+0      10000             1         2   total  0.000228   0.000025
+2      10000             2         2   total  0.001175   0.000127
+4      10000             3         2   total  0.001122   0.000122
+6      10000             4         2   total  0.011426   0.001099
+8      10000             5         2   total  0.004684   0.000451
+10     10000             6         2   total  0.001962   0.000189
    material  group in nuclide      mean  std. dev.
 1     10001         1   total  0.313738   0.015582
 0     10001         2   total  0.300821   0.028052
@@ -115,39 +154,39 @@
 1     10001         1   total  0.310121   0.033788
 0     10001         2   total  0.296264   0.043792
     material  group in  group out nuclide moment      mean  std. dev.
-12     10001         1          1   total     P0  0.310121   0.033788
-13     10001         1          1   total     P1  0.038230   0.008484
-14     10001         1          1   total     P2  0.020745   0.004696
+9      10001         1          1   total     P0  0.000000   0.000000
+11     10001         1          1   total     P1  0.000000   0.000000
+13     10001         1          1   total     P2  0.038230   0.008484
 15     10001         1          1   total     P3  0.007964   0.003732
 8      10001         1          2   total     P0  0.000000   0.000000
-9      10001         1          2   total     P1  0.000000   0.000000
-10     10001         1          2   total     P2  0.000000   0.000000
-11     10001         1          2   total     P3  0.000000   0.000000
-4      10001         2          1   total     P0  0.000000   0.000000
-5      10001         2          1   total     P1  0.000000   0.000000
-6      10001         2          1   total     P2  0.000000   0.000000
+10     10001         1          2   total     P1  0.000000   0.000000
+12     10001         1          2   total     P2  0.310121   0.033788
+14     10001         1          2   total     P3  0.020745   0.004696
+1      10001         2          1   total     P0 -0.011214   0.016180
+3      10001         2          1   total     P1 -0.003270   0.007329
+5      10001         2          1   total     P2  0.000000   0.000000
 7      10001         2          1   total     P3  0.000000   0.000000
 0      10001         2          2   total     P0  0.296264   0.043792
-1      10001         2          2   total     P1 -0.011214   0.016180
-2      10001         2          2   total     P2  0.008837   0.011504
-3      10001         2          2   total     P3 -0.003270   0.007329
+2      10001         2          2   total     P1  0.008837   0.011504
+4      10001         2          2   total     P2  0.000000   0.000000
+6      10001         2          2   total     P3  0.000000   0.000000
     material  group in  group out nuclide moment      mean  std. dev.
-12     10001         1          1   total     P0  0.310121   0.033788
-13     10001         1          1   total     P1  0.038230   0.008484
-14     10001         1          1   total     P2  0.020745   0.004696
+9      10001         1          1   total     P0  0.000000   0.000000
+11     10001         1          1   total     P1  0.000000   0.000000
+13     10001         1          1   total     P2  0.038230   0.008484
 15     10001         1          1   total     P3  0.007964   0.003732
 8      10001         1          2   total     P0  0.000000   0.000000
-9      10001         1          2   total     P1  0.000000   0.000000
-10     10001         1          2   total     P2  0.000000   0.000000
-11     10001         1          2   total     P3  0.000000   0.000000
-4      10001         2          1   total     P0  0.000000   0.000000
-5      10001         2          1   total     P1  0.000000   0.000000
-6      10001         2          1   total     P2  0.000000   0.000000
+10     10001         1          2   total     P1  0.000000   0.000000
+12     10001         1          2   total     P2  0.310121   0.033788
+14     10001         1          2   total     P3  0.020745   0.004696
+1      10001         2          1   total     P0 -0.011214   0.016180
+3      10001         2          1   total     P1 -0.003270   0.007329
+5      10001         2          1   total     P2  0.000000   0.000000
 7      10001         2          1   total     P3  0.000000   0.000000
 0      10001         2          2   total     P0  0.296264   0.043792
-1      10001         2          2   total     P1 -0.011214   0.016180
-2      10001         2          2   total     P2  0.008837   0.011504
-3      10001         2          2   total     P3 -0.003270   0.007329
+2      10001         2          2   total     P1  0.008837   0.011504
+4      10001         2          2   total     P2  0.000000   0.000000
+6      10001         2          2   total     P3  0.000000   0.000000
    material  group in  group out nuclide  mean  std. dev.
 3     10001         1          1   total   1.0   0.108779
 2     10001         1          2   total   0.0   0.000000
@@ -170,6 +209,45 @@
    material  group in nuclide  mean  std. dev.
 1     10001         1   total   0.0        0.0
 0     10001         2   total   0.0        0.0
+    material  delayedgroup  group in nuclide  mean  std. dev.
+1      10001             1         1   total   0.0        0.0
+3      10001             2         1   total   0.0        0.0
+5      10001             3         1   total   0.0        0.0
+7      10001             4         1   total   0.0        0.0
+9      10001             5         1   total   0.0        0.0
+11     10001             6         1   total   0.0        0.0
+0      10001             1         2   total   0.0        0.0
+2      10001             2         2   total   0.0        0.0
+4      10001             3         2   total   0.0        0.0
+6      10001             4         2   total   0.0        0.0
+8      10001             5         2   total   0.0        0.0
+10     10001             6         2   total   0.0        0.0
+    material  delayedgroup  group out nuclide  mean  std. dev.
+1      10001             1          1   total   0.0        0.0
+3      10001             2          1   total   0.0        0.0
+5      10001             3          1   total   0.0        0.0
+7      10001             4          1   total   0.0        0.0
+9      10001             5          1   total   0.0        0.0
+11     10001             6          1   total   0.0        0.0
+0      10001             1          2   total   0.0        0.0
+2      10001             2          2   total   0.0        0.0
+4      10001             3          2   total   0.0        0.0
+6      10001             4          2   total   0.0        0.0
+8      10001             5          2   total   0.0        0.0
+10     10001             6          2   total   0.0        0.0
+    material  delayedgroup  group in nuclide  mean  std. dev.
+1      10001             1         1   total   0.0        0.0
+3      10001             2         1   total   0.0        0.0
+5      10001             3         1   total   0.0        0.0
+7      10001             4         1   total   0.0        0.0
+9      10001             5         1   total   0.0        0.0
+11     10001             6         1   total   0.0        0.0
+0      10001             1         2   total   0.0        0.0
+2      10001             2         2   total   0.0        0.0
+4      10001             3         2   total   0.0        0.0
+6      10001             4         2   total   0.0        0.0
+8      10001             5         2   total   0.0        0.0
+10     10001             6         2   total   0.0        0.0
    material  group in nuclide      mean  std. dev.
 1     10002         1   total  0.664572   0.031215
 0     10002         2   total  2.052384   0.224343
@@ -201,39 +279,39 @@
 1     10002         1   total  0.671269   0.026186
 0     10002         2   total  2.035388   0.258060
     material  group in  group out nuclide moment      mean  std. dev.
-12     10002         1          1   total     P0  0.639901   0.024709
-13     10002         1          1   total     P1  0.381167   0.016243
-14     10002         1          1   total     P2  0.152392   0.008156
+9      10002         1          1   total     P0  0.008758   0.000926
+11     10002         1          1   total     P1 -0.003785   0.000817
+13     10002         1          1   total     P2  0.381167   0.016243
 15     10002         1          1   total     P3  0.009148   0.003889
 8      10002         1          2   total     P0  0.031368   0.001728
-9      10002         1          2   total     P1  0.008758   0.000926
-10     10002         1          2   total     P2 -0.002568   0.001014
-11     10002         1          2   total     P3 -0.003785   0.000817
-4      10002         2          1   total     P0  0.000443   0.000445
-5      10002         2          1   total     P1  0.000400   0.000401
-6      10002         2          1   total     P2  0.000320   0.000321
+10     10002         1          2   total     P1 -0.002568   0.001014
+12     10002         1          2   total     P2  0.639901   0.024709
+14     10002         1          2   total     P3  0.152392   0.008156
+1      10002         2          1   total     P0  0.509941   0.051236
+3      10002         2          1   total     P1  0.024988   0.008312
+5      10002         2          1   total     P2  0.000400   0.000401
 7      10002         2          1   total     P3  0.000214   0.000215
 0      10002         2          2   total     P0  2.034945   0.257800
-1      10002         2          2   total     P1  0.509941   0.051236
-2      10002         2          2   total     P2  0.111175   0.013020
-3      10002         2          2   total     P3  0.024988   0.008312
+2      10002         2          2   total     P1  0.111175   0.013020
+4      10002         2          2   total     P2  0.000443   0.000445
+6      10002         2          2   total     P3  0.000320   0.000321
     material  group in  group out nuclide moment      mean  std. dev.
-12     10002         1          1   total     P0  0.639901   0.024709
-13     10002         1          1   total     P1  0.381167   0.016243
-14     10002         1          1   total     P2  0.152392   0.008156
+9      10002         1          1   total     P0  0.008758   0.000926
+11     10002         1          1   total     P1 -0.003785   0.000817
+13     10002         1          1   total     P2  0.381167   0.016243
 15     10002         1          1   total     P3  0.009148   0.003889
 8      10002         1          2   total     P0  0.031368   0.001728
-9      10002         1          2   total     P1  0.008758   0.000926
-10     10002         1          2   total     P2 -0.002568   0.001014
-11     10002         1          2   total     P3 -0.003785   0.000817
-4      10002         2          1   total     P0  0.000443   0.000445
-5      10002         2          1   total     P1  0.000400   0.000401
-6      10002         2          1   total     P2  0.000320   0.000321
+10     10002         1          2   total     P1 -0.002568   0.001014
+12     10002         1          2   total     P2  0.639901   0.024709
+14     10002         1          2   total     P3  0.152392   0.008156
+1      10002         2          1   total     P0  0.509941   0.051236
+3      10002         2          1   total     P1  0.024988   0.008312
+5      10002         2          1   total     P2  0.000400   0.000401
 7      10002         2          1   total     P3  0.000214   0.000215
 0      10002         2          2   total     P0  2.034945   0.257800
-1      10002         2          2   total     P1  0.509941   0.051236
-2      10002         2          2   total     P2  0.111175   0.013020
-3      10002         2          2   total     P3  0.024988   0.008312
+2      10002         2          2   total     P1  0.111175   0.013020
+4      10002         2          2   total     P2  0.000443   0.000445
+6      10002         2          2   total     P3  0.000320   0.000321
    material  group in  group out nuclide  mean  std. dev.
 3     10002         1          1   total   1.0   0.038609
 2     10002         1          2   total   1.0   0.067667
@@ -256,3 +334,42 @@
    material  group in nuclide  mean  std. dev.
 1     10002         1   total   0.0        0.0
 0     10002         2   total   0.0        0.0
+    material  delayedgroup  group in nuclide  mean  std. dev.
+1      10002             1         1   total   0.0        0.0
+3      10002             2         1   total   0.0        0.0
+5      10002             3         1   total   0.0        0.0
+7      10002             4         1   total   0.0        0.0
+9      10002             5         1   total   0.0        0.0
+11     10002             6         1   total   0.0        0.0
+0      10002             1         2   total   0.0        0.0
+2      10002             2         2   total   0.0        0.0
+4      10002             3         2   total   0.0        0.0
+6      10002             4         2   total   0.0        0.0
+8      10002             5         2   total   0.0        0.0
+10     10002             6         2   total   0.0        0.0
+    material  delayedgroup  group out nuclide  mean  std. dev.
+1      10002             1          1   total   0.0        0.0
+3      10002             2          1   total   0.0        0.0
+5      10002             3          1   total   0.0        0.0
+7      10002             4          1   total   0.0        0.0
+9      10002             5          1   total   0.0        0.0
+11     10002             6          1   total   0.0        0.0
+0      10002             1          2   total   0.0        0.0
+2      10002             2          2   total   0.0        0.0
+4      10002             3          2   total   0.0        0.0
+6      10002             4          2   total   0.0        0.0
+8      10002             5          2   total   0.0        0.0
+10     10002             6          2   total   0.0        0.0
+    material  delayedgroup  group in nuclide  mean  std. dev.
+1      10002             1         1   total   0.0        0.0
+3      10002             2         1   total   0.0        0.0
+5      10002             3         1   total   0.0        0.0
+7      10002             4         1   total   0.0        0.0
+9      10002             5         1   total   0.0        0.0
+11     10002             6         1   total   0.0        0.0
+0      10002             1         2   total   0.0        0.0
+2      10002             2         2   total   0.0        0.0
+4      10002             3         2   total   0.0        0.0
+6      10002             4         2   total   0.0        0.0
+8      10002             5         2   total   0.0        0.0
+10     10002             6         2   total   0.0        0.0

tests/test_mgxs_library_no_nuclides/test_mgxs_library_no_nuclides.py

@@ -23,12 +23,18 @@ class MGXSTestHarness(PyAPITestHarness):
         energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 0.625e-6,
                                                               20.])
 
+        # Initialize a six-delayed-group structure
+        delayed_groups = list(range(1,7))
+
         # Initialize MGXS Library for a few cross section types
         self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry)
         self.mgxs_lib.by_nuclide = False
+
         # Test all MGXS types
-        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES
+        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES + \
+                                   openmc.mgxs.MDGXS_TYPES
         self.mgxs_lib.energy_groups = energy_groups
+        self.mgxs_lib.delayed_groups = delayed_groups
         self.mgxs_lib.legendre_order = 3
         self.mgxs_lib.domain_type = 'material'
         self.mgxs_lib.build_library()

tests/test_mgxs_library_nuclides/results_true.dat

@@ -1 +1 @@
-e494320a213b5704a2ac915a2ba504857be91961ceb6735b6ad05d81eb31c44c9584d5bd9d40baececf1dcb5b030e6ecec63cfbd20639baf69bcb596c5c46591
+8142ae4e107002a835999e4ace85c17376f262a7059fc224f3756a2de19aba6ca4c4fa14ca2085c87d7729aa8d6d6f78fdae21ac6dfe33ca303449c769076074

tests/test_score_current/results_true.dat

@@ -1 +1 @@
-bafab1921a12146abb2bb29603b52b9cc28a5a950a7a6bb1e3f012c05891c310fad643760d4f148b04d0fef3d1f3e141d146e3a278d81cc6fc8187c37717c5e7
+c2921f159dac64099862c1cd9c6d421c977991f621f954f893ec1351cfcea6794ca2c98c9c2dcc3411f1b8dac91ec83bd895788ba33179222c450a7df1d64f1e

tests/test_tallies/results_true.dat

@@ -1 +1 @@
-5a0f3f1ae244ada7d8c9f444d7a98c2589a9720e78174a276cf96162df6728bab6d534f136f65cb0386c3235eb7d5db47a0dd6504636ca77e7eb375e6978a84d
+a6afd2f11affce2467d77b8477881ab20091f67df4f632226ec2dd5d4cd7fabb9ac3e182563bb467ed249e4b3fe95b319cb688d653757f8ea154759b8a7f50e1

tests/test_tally_slice_merge/results_true.dat

@@ -49,19 +49,19 @@
 14     (500, 5000, 50000)          6.25e-07           2.00e+01    U238     fission 0.00e+00   0.00e+00
 15     (500, 5000, 50000)          6.25e-07           2.00e+01    U238  nu-fission 0.00e+00   0.00e+00
                  sum(mesh)  energy low [MeV]  energy high [MeV] nuclide       score     mean  std. dev.
-0   ((1, 1, 1), (1, 2, 1))          0.00e+00           6.25e-07    U235     fission 9.18e-03   1.62e-03
-1   ((1, 1, 1), (1, 2, 1))          0.00e+00           6.25e-07    U235  nu-fission 2.24e-02   3.94e-03
-2   ((1, 1, 1), (1, 2, 1))          0.00e+00           6.25e-07    U238     fission 1.31e-08   2.08e-09
-3   ((1, 1, 1), (1, 2, 1))          0.00e+00           6.25e-07    U238  nu-fission 3.26e-08   5.19e-09
-4   ((1, 1, 1), (1, 2, 1))          6.25e-07           2.00e+01    U235     fission 8.40e-04   2.13e-04
-5   ((1, 1, 1), (1, 2, 1))          6.25e-07           2.00e+01    U235  nu-fission 2.06e-03   5.17e-04
-6   ((1, 1, 1), (1, 2, 1))          6.25e-07           2.00e+01    U238     fission 7.05e-04   3.42e-04
-7   ((1, 1, 1), (1, 2, 1))          6.25e-07           2.00e+01    U238  nu-fission 1.99e-03   1.01e-03
-8   ((2, 1, 1), (2, 2, 1))          0.00e+00           6.25e-07    U235     fission 8.77e-03   1.30e-03
-9   ((2, 1, 1), (2, 2, 1))          0.00e+00           6.25e-07    U235  nu-fission 2.14e-02   3.18e-03
-10  ((2, 1, 1), (2, 2, 1))          0.00e+00           6.25e-07    U238     fission 1.24e-08   1.74e-09
-11  ((2, 1, 1), (2, 2, 1))          0.00e+00           6.25e-07    U238  nu-fission 3.08e-08   4.33e-09
-12  ((2, 1, 1), (2, 2, 1))          6.25e-07           2.00e+01    U235     fission 2.30e-03   6.20e-04
-13  ((2, 1, 1), (2, 2, 1))          6.25e-07           2.00e+01    U235  nu-fission 5.63e-03   1.52e-03
-14  ((2, 1, 1), (2, 2, 1))          6.25e-07           2.00e+01    U238     fission 1.45e-03   7.19e-04
-15  ((2, 1, 1), (2, 2, 1))          6.25e-07           2.00e+01    U238  nu-fission 3.97e-03   1.98e-03
+0   ((1, 1, 1), (1, 2, 1))          0.00e+00           6.25e-07    U235     fission 8.54e-03   1.30e-03
+1   ((1, 1, 1), (1, 2, 1))          0.00e+00           6.25e-07    U235  nu-fission 2.08e-02   3.17e-03
+2   ((1, 1, 1), (1, 2, 1))          0.00e+00           6.25e-07    U238     fission 1.21e-08   1.74e-09
+3   ((1, 1, 1), (1, 2, 1))          0.00e+00           6.25e-07    U238  nu-fission 3.01e-08   4.34e-09
+4   ((1, 1, 1), (1, 2, 1))          6.25e-07           2.00e+01    U235     fission 2.20e-03   6.05e-04
+5   ((1, 1, 1), (1, 2, 1))          6.25e-07           2.00e+01    U235  nu-fission 5.38e-03   1.48e-03
+6   ((1, 1, 1), (1, 2, 1))          6.25e-07           2.00e+01    U238     fission 1.40e-03   7.17e-04
+7   ((1, 1, 1), (1, 2, 1))          6.25e-07           2.00e+01    U238  nu-fission 3.84e-03   1.97e-03
+8   ((2, 1, 1), (2, 2, 1))          0.00e+00           6.25e-07    U235     fission 9.40e-03   1.62e-03
+9   ((2, 1, 1), (2, 2, 1))          0.00e+00           6.25e-07    U235  nu-fission 2.29e-02   3.95e-03
+10  ((2, 1, 1), (2, 2, 1))          0.00e+00           6.25e-07    U238     fission 1.34e-08   2.08e-09
+11  ((2, 1, 1), (2, 2, 1))          0.00e+00           6.25e-07    U238  nu-fission 3.33e-08   5.18e-09
+12  ((2, 1, 1), (2, 2, 1))          6.25e-07           2.00e+01    U235     fission 9.41e-04   2.52e-04
+13  ((2, 1, 1), (2, 2, 1))          6.25e-07           2.00e+01    U235  nu-fission 2.31e-03   6.13e-04
+14  ((2, 1, 1), (2, 2, 1))          6.25e-07           2.00e+01    U238     fission 7.54e-04   3.45e-04
+15  ((2, 1, 1), (2, 2, 1))          6.25e-07           2.00e+01    U238  nu-fission 2.12e-03   1.02e-03

tests/test_track_output/results_true.dat

@@ -1,5 +1,5 @@
 <?xml version="1.0"?>
-<VTKFile type="PPolyData" version="0.1" byte_order="LittleEndian" compressor="vtkZLibDataCompressor">
+<VTKFile type="PPolyData" version="0.1" byte_order="LittleEndian" header_type="UInt32" compressor="vtkZLibDataCompressor">
   <PPolyData GhostLevel="0">
     <PPoints>
       <PDataArray type="Float32" Name="Points" NumberOfComponents="3"/>